Interactive
Every possible 2026 season
Twelve games have 4,096 outcomes. This prices all of them — exactly, not by simulation — from the same opponent-adjusted ratings published in the Data Lab. Then you get to argue with it.
8-4
Most likely
24.9%
7.6
Expected wins
of 12
91.1%
Bowl eligible
6+ wins
0.2%
Undefeated
12-0
Building the landscape…
Where the season ends
The chance of each final record, across all 4096 possible sequences.
- 12-00.2%
- 11-12.0%
- 10-27.8%
- 9-317.5%
- 8-424.9%
- 7-523.6%
- 6-615.1%
- 5-76.6%
- 4-81.9%
- 3-90.3%
Change something
Force a result, or decide this team is better than the ratings think. Everything above recomputes instantly.
−10 worseas rated+10 better
- Wk 1vs Furmanunrated99.9%
- Wk 2@ Georgia Tech71.3%
- Wk 3vs Kennesaw State90.1%
- Wk 4vs Texas43.3%
- Wk 5vs Auburn69.4%
- Wk 6@ Arkansas72.8%
- Wk 7vs Alabama29.4%
- Wk 8@ South Carolina51.7%
- Wk 10vs Kentucky67.8%
- Wk 11@ Texas A&M44.2%
- Wk 12vs LSU50.9%
- Wk 13@ Vanderbilt66.1%
Share the run
The straight model output, as text.
All 4096 possible Tennessee 2026 seasons, priced by opponent-adjusted ratings: Most likely: 8-4 (24.9%) Expected wins: 7.6 Bowl eligible (6+): 91.1% Undefeated: 0.2% https://voluntarytakes.com/season-simulator?s=0000a
How this works
Each game starts as a predicted margin: Tennessee's rating minus the opponent's, plus 2.5 points for playing at home or minus 2.5 for playing away. Both ratings are opponent-adjusted — they already account for who each team played.
Turning a margin into a win probability needs to know what a point of margin is actually worth. That relationship isn't assumed here. Nothing has been measured for this season yet, so a documented default of 13.0 points is standing in, and this note is here rather than a silent substitution.
That fitted number replaced an earlier one, and the change matters. The model used to convert margins using its average margin error, which is a different question and made it far too timid about heavy favorites — it said 85% for games favorites won 98% of the time. Measuring the relationship against outcomes instead cut the average calibration miss roughly in half on held-out games. The before and after is published.
The season is then rolled forward exactly. There is no random simulation and no sample noise: every reachable record gets its true probability, which is why the same inputs always give the same answer and why the whole thing recomputes the instant you change something.
Opponents outside the ratings pool — Furman, and any other FCS team — are given the engine's standard non-FBS rating rather than being guessed at individually.
This is not a prediction. It is the arithmetic consequence of one rating system's numbers, built on 2026 results for a season that has not started. Rosters turn over, players get hurt, and a one-score game is close to a coin flip whatever any model says. It is not betting advice.