Hawaii’s third-down conversion rate with Cam Barfield and without Cam Barfield
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Against what the season’s ratings expected, Hawaii was 1.2 percentage points over with Cam Barfield and 0.4 percentage points over without Cam Barfield over its last 25 games, 22 games against 2. The plain averages are 41.0% and 39.2%, a difference of 1.8%. All 11 away games were with Cam Barfield. All 7 night games were with Cam Barfield. All 5 games after a bye were with Cam Barfield.
Cam Barfield, running back: 583 rushing yards, 136 carries and 41 receptions in 23 of those 25 games.
2 games without Cam Barfield 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 +0.8% difference in third-down conversion rate over expected with Cam Barfield vs without Cam Barfield is about what you’d expect.
A +1.8% difference in third-down conversion rate with Cam Barfield vs without Cam Barfield is about what you’d expect.
The games
| Side | Date | Game | Result | 3rd downs | Expected |
|---|---|---|---|---|---|
| Nov 2, 2024 | @ Fresno State | W | 35.0% | 31.3% | |
| Nov 9, 2024 | vs UNLV | L | 21.4% | 31.1% | |
| Nov 16, 2024 | @ Utah State | L | 28.6% | 38.7% | |
| Nov 30, 2024 | vs New Mexico | W | 62.5% | 37.9% | |
| Aug 23, 2025 | vs Stanford | W | 30.0% | 41.3% | |
| Aug 30, 2025 | @ Arizona | L | 28.6% | 38.8% | |
| Sep 6, 2025 | vs Sam Houston | W | 35.3% | 47.9% | |
| Sep 13, 2025 | vsPPortland State | W | 47.4% | — | |
| Sep 20, 2025 | vsFresno State | L | 41.2% | 41.3% | |
| Sep 27, 2025 | @ Air Force | W | 73.7% | 44.8% | |
| Oct 11, 2025 | vsUtah State | W | 31.3% | 42.5% | |
| Oct 18, 2025 | @ Colorado State | W | 50.0% | 45.6% | |
| Nov 1, 2025 | @ San Jose State | L | 64.3% | 37.2% | |
| Nov 8, 2025 | vs San Diego State | W | 52.9% | 37.1% | |
| Nov 21, 2025 | @UNLV | L | 30.0% | 37.7% | |
| Nov 29, 2025 | vs Wyoming | W | 35.7% | 40.3% | |
| Dec 24, 2025 | vs California | W | 47.1% | 43.3% | |
| Aug 29, 2026 | @Stanford | L | 42.1% | 41.7% | |
| Sep 5, 2026 | vsUNLV | L | 45.0% | 37.8% | |
| Sep 12, 2026 | vs New Mexico State | W | 33.3% | 39.7% | |
| Sep 26, 2026 | @Wyoming | L | 35.7% | 37.7% | |
| Oct 3, 2026 | vsSan Jose State | L | 30.8% | 38.1% | |
| Oct 10, 2026 | @ Arizona State | L | 36.8% | 32.4% | |
| Oct 17, 2026 | vsNew Mexico | L | 23.1% | 40.5% | |
| Oct 24, 2026 | @ Northern Illinois | W | 60.0% | 43.0% |
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.
- Portland State 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 for 21 of these 25 games; in the other 4 a player is counted as in them when the box score has a stat for him.