What If Every One-Score Game Were a Tie?
A 761-game stress test that re-ranks the 2025 FBS season after turning every result decided by seven points or fewer into half a win and half a loss.
By Rankrly Research · Published August 31, 2026
Close wins receive the same full credit as blowouts in a wins-and-losses ranking. That makes a simple counterfactual useful: keep the schedule intact, but turn every one-score result into half a win and half a loss.
This does not claim close games are random. It measures how dependent each team’s rating is on getting the full outcome from games that finished within one possession.
The answer
Texas Tech becomes #1. Auburn climbs 48 places. Tulane falls 31.
Texas Tech’s only FBS loss was within seven points, so the stress test turns an 11-1 FBS record into an 11-0-1 adjusted record. Auburn’s six one-score losses become ties, moving the Tigers from #73 to #25. Tulane’s five one-score wins lose half a win each, dropping the Green Wave from #13 to #44.
761
FBS games analyzed
264
one-score games
34.7%
of the dataset
6
Top 25 replacements
Interactive results
Change the definition and inspect every team
Switch between three, seven, and ten points. The gray dot is the baseline Colley rank; the blue dot is the rank after qualifying games become ties.
Biggest rises
Close losses stop carrying the full penalty
Arkansas
0-6 in one-score games
#111 → #61
Auburn
0-6 in one-score games
#73 → #25
Kansas State
0-5 in one-score games
#61 → #16
Washington State
0-4 in one-score games
#67 → #32
Penn State
1-5 in one-score games
#57 → #28
Florida State
0-3 in one-score games
#81 → #53
Biggest falls
Perfect close-game records lose their leverage
California
4-0 in one-score games
#60 → #97
Kennesaw State
5-1 in one-score games
#36 → #72
Tulane
5-0 in one-score games
#13 → #44
Troy
3-0 in one-score games
#65 → #95
Arizona State
5-1 in one-score games
#27 → #54
Rice
3-1 in one-score games
#94 → #121
Seven-point scenario
The stress-tested Top 25
Six teams enter and six leave, showing how aggressively close results reshape the edge of the Top 25.
Entered
Iowa, Kansas State, Louisville, Pittsburgh, SMU, Auburn
Exited
Tulane, Michigan, North Texas, Texas, Navy, Illinois
- #1+7
Texas Tech
Big 12
- Baseline
- #8
- Actual record
- 11-1
- Adjusted record
- 11-0-1
- #20
Ohio State
Big Ten
- Baseline
- #2
- Actual record
- 11-1
- Adjusted record
- 10-0-2
- #3+7
Notre Dame
FBS Independents
- Baseline
- #10
- Actual record
- 10-2
- Adjusted record
- 10-0-2
- #4-3
Indiana
Big Ten
- Baseline
- #1
- Actual record
- 12-0
- Adjusted record
- 9-0-3
- #5-2
Georgia
SEC
- Baseline
- #3
- Actual record
- 11-1
- Adjusted record
- 8-0-4
- #6+6
Miami
ACC
- Baseline
- #12
- Actual record
- 9-2
- Adjusted record
- 7-0-4
- #7+7
Utah
Big 12
- Baseline
- #14
- Actual record
- 9-2
- Adjusted record
- 8-1-2
- #8-4
Oregon
Big Ten
- Baseline
- #4
- Actual record
- 10-1
- Adjusted record
- 8-1-2
- #9-4
BYU
Big 12
- Baseline
- #5
- Actual record
- 10-2
- Adjusted record
- 7-2-3
- #10-3
Texas A&M
SEC
- Baseline
- #7
- Actual record
- 10-1
- Adjusted record
- 6-1-4
- #11-5
Ole Miss
SEC
- Baseline
- #6
- Actual record
- 10-1
- Adjusted record
- 6-1-4
- #12+17
Iowa
Big Ten
- Baseline
- #29
- Actual record
- 7-4
- Adjusted record
- 5-0-6
- #13+2
Vanderbilt
SEC
- Baseline
- #15
- Actual record
- 9-2
- Adjusted record
- 6-1-4
- #14+3
James Madison
Sun Belt
- Baseline
- #17
- Actual record
- 11-1
- Adjusted record
- 9-1-2
- #15+1
USC
Big Ten
- Baseline
- #16
- Actual record
- 9-3
- Adjusted record
- 7-2-3
- #16+45
Kansas State
Big 12
- Baseline
- #61
- Actual record
- 5-6
- Adjusted record
- 5-1-5
- #17+6
Virginia
ACC
- Baseline
- #23
- Actual record
- 9-3
- Adjusted record
- 6-0-6
- #18+4
Arizona
Big 12
- Baseline
- #22
- Actual record
- 8-3
- Adjusted record
- 5-1-5
- #19-8
Alabama
SEC
- Baseline
- #11
- Actual record
- 9-3
- Adjusted record
- 5-2-5
- #20+5
South Florida
American Athletic
- Baseline
- #25
- Actual record
- 8-3
- Adjusted record
- 7-1-3
- #21+17
Louisville
ACC
- Baseline
- #38
- Actual record
- 7-4
- Adjusted record
- 5-1-5
- #22+17
Pittsburgh
ACC
- Baseline
- #39
- Actual record
- 7-4
- Adjusted record
- 6-2-3
- #23+20
SMU
ACC
- Baseline
- #43
- Actual record
- 7-4
- Adjusted record
- 6-1-4
- #24-15
Oklahoma
SEC
- Baseline
- #9
- Actual record
- 9-2
- Adjusted record
- 5-2-4
- #25+48
Auburn
SEC
- Baseline
- #73
- Actual record
- 4-7
- Adjusted record
- 4-1-6
Why Texas Tech reaches #1
Its only FBS loss becomes a tie, changing its FBS record from 11-1 to 11-0-1 while keeping every opponent connection in the matrix.
Why Auburn reaches #25
Six one-score losses become ties. The FBS record moves from 4-7 to 4-1-6 against the same schedule.
Why Tulane falls to #44
Five one-score wins become ties, removing 2.5 wins of close-game dependency from the baseline result.
Methodology
One schedule, four complete rankings
How the ranking works, in plain English
The Colley Matrix starts every team at the same neutral rating. Actual wins and losses move that rating, while the schedule connections determine how much each result affects the rest of the field.
For a selected threshold, every qualifying close result becomes half a win and half a loss for both teams. A 7-5 team with two close wins is displayed as 5-5-2, while the Colley calculation receives six win credits and six loss credits.
The model then recalculates all 136 ratings together. A team can move because its own record changed, because an opponent changed, or because both changes ripple through the schedule network.
Teams are sorted by the recalculated rating. The displayed rank change is the difference between that stress rank and the same Colley calculation using the actual FBS results.
Use every completed 2025 regular-season game between two FBS teams through provider Week 15, which ends with conference championship weekend.
Exclude FCS opponents, bowls, playoff games, and the Week 16 Army-Navy game so the dataset reflects results available for playoff selection.
Build a baseline Colley Matrix from the actual wins and losses. The method uses game results and opponent connections without margin of victory, preseason expectations, or conference weights.
Run three stress scenarios. Games decided by three, seven, or ten points become ties worth half a win and half a loss to each team. Every other result stays unchanged.
Rebuild the full schedule matrix after each treatment, then rank all 136 teams by their resulting Colley rating.
Define rank change as baseline rank minus stress-test rank. Positive values indicate a rise after close results are neutralized.
What this does not prove
Sensitivity is not the same as luck
Close-game dependency is not proof of luck. Coaching, quarterback play, special teams, and repeatable late-game skill can affect close outcomes.
The tie treatment intentionally removes information. A seven-point win is not literally equivalent to a tie; the scenario measures ranking sensitivity to that assumption.
FCS games are excluded completely. This keeps opponent classifications consistent but means displayed records differ from each team’s official overall record.
Rank movement can come from both a team’s own close games and changes to its opponents’ ratings, because the matrix recalculates the entire schedule together.
Sources and reproducibility
Game data and ranking method
The results cover all 136 FBS teams across the three-, seven-, and ten-point scenarios. Every table and chart uses the same 761-game FBS-only dataset.