Virginia Tech’s third-down conversion rate with Ayden Greene and without Ayden Greene
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Against what the season’s ratings expected, Virginia Tech was 0.0 percentage points over with Ayden Greene and 15.3 percentage points under without Ayden Greene over its last 25 games, 21 games against 2. The plain averages are 38.9% and 20.5%, a difference of 18.4%. All 13 home games were with Ayden Greene. Both neutral-site games were with Ayden Greene. All 12 night games were with Ayden Greene.
Ayden Greene, receiver: 981 receiving yards, 60 receptions and 6 receiving touchdowns in 23 of those 25 games.
2 games without Ayden Greene is still too small a sample for the statistics to say much, but maybe you can find something if you squint.
third-down conversion rate a game over expected
A +15.3% difference in third-down conversion rate over expected with Ayden Greene vs without Ayden Greene is about what you’d expect.
A +18.4% difference in third-down conversion rate with Ayden Greene vs without Ayden Greene is about what you’d expect.
The games
| Side | Date | Game | Result | 3rd downs | Expected |
|---|---|---|---|---|---|
| Nov 2, 2024 | @ Syracuse | L | 45.5% | 35.5% | |
| Nov 9, 2024 | vs Clemson | L | 14.3% | 37.9% | |
| Nov 23, 2024 | @ Duke | L | 31.6% | 36.0% | |
| Nov 30, 2024 | vs Virginia | W | 46.2% | 36.8% | |
| Jan 3, 2025 | vs Minnesota (neutral) | L | 27.3% | 37.1% | |
| Aug 31, 2025 | vs South Carolina (neutral) | L | 44.4% | 37.0% | |
| Sep 6, 2025 | vs Vanderbilt | L | 42.9% | 42.4% | |
| Sep 13, 2025 | vs Old Dominion | L | 46.2% | 36.2% | |
| Sep 20, 2025 | vs Wofford | W | 54.5% | — | |
| Sep 27, 2025 | @ NC State | W | 46.7% | 40.3% | |
| Oct 4, 2025 | vs Wake Forest | L | 41.2% | 35.8% | |
| Oct 11, 2025 | @ Georgia Tech | L | 0.0% | 45.1% | |
| Oct 24, 2025 | vs California | W | 50.0% | 40.5% | |
| Nov 1, 2025 | vs Louisville | L | 26.7% | 36.6% | |
| Nov 15, 2025 | @ Florida State | L | 66.7% | 35.9% | |
| Nov 22, 2025 | vs Miami (FL) | L | 25.0% | 32.6% | |
| Nov 29, 2025 | @Virginia | L | 14.3% | 33.0% | |
| Sep 5, 2026 | vs VMI | W | 37.5% | — | |
| Sep 12, 2026 | vsOld Dominion | W | 47.6% | 37.9% | |
| Sep 19, 2026 | @ Maryland | W | 62.5% | 35.7% | |
| Sep 26, 2026 | @ Boston College | W | 26.7% | 38.6% | |
| Oct 2, 2026 | vs Pittsburgh | L | 37.5% | 40.8% | |
| Oct 10, 2026 | @California | L | 36.4% | 40.6% | |
| Oct 17, 2026 | vsGeorgia Tech | W | 30.8% | 46.9% | |
| Oct 24, 2026 | @Clemson | W | 33.3% | 34.2% |
Method
- Expected is an offense and a defense a team, fit over every game of its season between two teams in the table with the game being read left out, plus 0.6% in 2024, plus 0.7% in 2025, plus 1.4% in 2026 for the home team (the edge the fit finds once strength is in), nothing at a neutral site.
- Each expected number is then fit to the season’s games: a game bears out about 50% in 2024, 56% in 2025, 40% in 2026 of the difference the model predicts.
- The shuffle keeps the season’s shape: the games are cut in two where one date leaves the least variance, each game is read against its stretch, and the sides are shuffled only inside each stretch.
- Wofford, VMI have no other game in the table, so those games have no expected number and sit out the second figure.
- Who played is read from the schools’ box scores’ participation lists for 9 of these 25 games; in the other 16 a player is counted as in them when the box score has a stat for him.