Boston College’s third-down conversion rate with Nolan Ray and without Nolan Ray
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Against what the season’s ratings expected, Boston College was 3.5 percentage points over with Nolan Ray and 17.9 percentage points under without Nolan Ray over its last 25 games, 5 games against 2. The plain averages are 38.6% and 23.1%, a difference of 15.6%.
Nolan Ray, running back: 42 rushing yards, 7 carries and 1 reception in 4 of those 25 games.
2 games without Nolan Ray 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
with Nolan Ray
+3.5%
without Nolan Ray
−17.9%
-20%0%20%
A +21.3% difference in third-down conversion rate over expected with Nolan Ray vs without Nolan Ray is about what you’d expect.
plain
38.6%
23.1%
20%40%60%
A +15.6% difference in third-down conversion rate with Nolan Ray vs without Nolan Ray is about what you’d expect.
The games
with Nolan Raywithout Nolan Ray
| Side | Date | Game | Result | 3rd downs | Expected |
|---|---|---|---|---|---|
| Nov 9, 2024 | vs Syracuse | W | 30.8% | 43.0% | |
| Nov 16, 2024 | @ SMU | L | 40.0% | 38.7% | |
| Nov 23, 2024 | vs North Carolina | W | 46.7% | 42.0% | |
| Nov 30, 2024 | vs Pittsburgh | W | 35.7% | 40.4% | |
| Dec 28, 2024 | vs Nebraska (neutral) | L | 50.0% | 37.6% | |
| Aug 30, 2025 | vs Fordham | W | 66.7% | — | |
| Sep 6, 2025 | @ Michigan State | L | 45.5% | 36.2% | |
| Sep 13, 2025 | @ Stanford | L | 38.5% | 36.8% | |
| Sep 27, 2025 | vs California | L | 36.4% | 41.9% | |
| Oct 4, 2025 | @Pittsburgh | L | 33.3% | 34.8% | |
| Oct 11, 2025 | vs Clemson | L | 25.0% | 34.7% | |
| Oct 18, 2025 | vs UConn | L | 26.7% | 42.8% | |
| Oct 25, 2025 | @ Louisville | L | 37.5% | 34.2% | |
| Nov 1, 2025 | vs Notre Dame | L | 44.4% | 32.7% | |
| Nov 8, 2025 | vsSMU | L | 13.3% | 39.7% | |
| Nov 15, 2025 | vs Georgia Tech | L | 45.5% | 40.5% | |
| Nov 29, 2025 | @Syracuse | W | 50.0% | 36.8% | |
| Sep 5, 2026 | @ Cincinnati | L | 30.8% | 40.5% | |
| Sep 11, 2026 | vs Rutgers | W | 33.3% | 43.6% | |
| Sep 19, 2026 | vs Maine | W | 33.3% | — | |
| Sep 26, 2026 | vs Virginia Tech | L | 15.4% | 41.5% | |
| Oct 3, 2026 | @SMU | L | 43.8% | 29.9% | |
| Oct 17, 2026 | vsPittsburgh | W | 61.5% | 33.6% | |
| Oct 24, 2026 | @Georgia Tech | W | 44.4% | 39.6% | |
| Oct 31, 2026 | @ Duke | L | 15.4% | 34.6% |
Method
- Expected is an offense and a defense a team, fit over every 2026 game between two teams in the table with the game being read left out, plus 1.4% 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 40% 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.
- Maine has no other game in the table, so that game has no expected number and sits out the second figure.
- Who played is read from the schools’ box scores’ participation lists, which name every player who entered the game.
- 17 games in 2024 and 2025 are neither with Nolan Ray nor without Nolan Ray: Nolan Ray had no game for the team those seasons, and sit out.