California’s third-down conversion rate with Jaron-Keawe Sagapolutele and without Jaron-Keawe Sagapolutele
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Against what the season’s ratings expected, California was 0.8 percentage points under with Jaron-Keawe Sagapolutele and 1.1 percentage points under without Jaron-Keawe Sagapolutele over its last 25 games, 17 games against 3. The plain averages are 38.3% and 38.4%, a difference of 0.1%. Expected was 0.8 percentage points lower with Jaron-Keawe Sagapolutele than without Jaron-Keawe Sagapolutele. Both opponents outside the major colleges were with Jaron-Keawe Sagapolutele. Both games after a bye were with Jaron-Keawe Sagapolutele. All 11 of Justin Wilcox’s games were with Jaron-Keawe Sagapolutele.
Jaron-Keawe Sagapolutele, quarterback: 5,205 passing yards, 756 pass attempts and 494 completions in 21 of those 25 games.
3 games without Jaron-Keawe Sagapolutele 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 +0.3% difference in third-down conversion rate over expected with Jaron-Keawe Sagapolutele vs without Jaron-Keawe Sagapolutele is about what you’d expect.
A −0.1% difference in third-down conversion rate with Jaron-Keawe Sagapolutele vs without Jaron-Keawe Sagapolutele is a bit unusual: shuffle which games were with Jaron-Keawe Sagapolutele and it comes up 11 times in 100.
The games
| Side | Date | Game | Result | 3rd downs | Expected |
|---|---|---|---|---|---|
| Nov 23, 2024 | vs Stanford | W | 52.9% | 40.5% | |
| Nov 30, 2024 | @ SMU | L | 20.0% | 36.1% | |
| Dec 18, 2024 | vs UNLV (neutral) | L | 31.6% | 34.3% | |
| Aug 30, 2025 | @ Oregon State | W | 15.4% | 37.5% | |
| Sep 6, 2025 | vs Texas Southern | W | 50.0% | — | |
| Sep 13, 2025 | vs Minnesota | W | 46.2% | 42.2% | |
| Sep 20, 2025 | @ San Diego State | L | 35.3% | 37.8% | |
| Sep 27, 2025 | @ Boston College | W | 50.0% | 42.0% | |
| Oct 4, 2025 | vs Duke | L | 45.5% | 43.1% | |
| Oct 17, 2025 | vs North Carolina | W | 37.5% | 44.0% | |
| Oct 24, 2025 | @ Virginia Tech | L | 35.7% | 43.6% | |
| Nov 1, 2025 | vs Virginia | L | 25.0% | 34.7% | |
| Nov 8, 2025 | @ Louisville | W | 44.4% | 35.8% | |
| Nov 22, 2025 | @Stanford | L | 38.9% | 39.1% | |
| Nov 29, 2025 | vsSMU | W | 53.8% | 37.4% | |
| Dec 24, 2025 | @ Hawaii | L | 55.6% | 40.1% | |
| Sep 5, 2026 | vs UCLA | L | 52.4% | 31.0% | |
| Sep 12, 2026 | @ Syracuse | W | 25.0% | 40.5% | |
| Sep 19, 2026 | vsWWagner | W | 33.3% | — | |
| Sep 25, 2026 | vs Clemson | L | 25.0% | 35.4% | |
| Oct 3, 2026 | @UNLV | L | 27.8% | 41.3% | |
| Oct 10, 2026 | vsVirginia Tech | W | 50.0% | 38.3% | |
| Oct 17, 2026 | vs Wake Forest | L | 37.5% | 38.8% | |
| Oct 24, 2026 | @SMU | L | 31.3% | 34.1% | |
| Oct 31, 2026 | @ NC State | L | 27.8% | 39.5% |
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 0.7% 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 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.
- Texas Southern, Wagner 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, which name every player who entered the game.
- With him means he was the team’s quarterback that game, at least half of its pass attempts; a game he left early or came into late reads as without him.
- 3 games in 2024 are neither with Jaron-Keawe Sagapolutele nor without Jaron-Keawe Sagapolutele: Jaron-Keawe Sagapolutele had no game for the team that season, and sit out.