The Commanders' points of margin with Jeremy McNichols and without Jeremy McNichols
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Against what the season’s ratings expected, the Commanders were 0.7 points under with Jeremy McNichols and 6.5 points under without Jeremy McNichols over their last 35 games, 30 games against 5. The plain averages are -2.6 and -6.8, a difference of 4.2. All 3 games after a bye were with Jeremy McNichols. Both games on a short week were with Jeremy McNichols. All 3 playoff games were with Jeremy McNichols.
Jeremy McNichols, running back: 342 rushing yards, 80 carries and 34 receptions in 28 of those 35 games.
points of margin a game over expected
A +5.8 difference in points of margin over expected with Jeremy McNichols vs without Jeremy McNichols is about what you’d expect.
A +4.2 difference in points of margin with Jeremy McNichols vs without Jeremy McNichols is about what you’d expect.
The games
| Side | Date | Game | Result | points of margin | Expected |
|---|---|---|---|---|---|
| Nov 10, 2024 | vs PIT | L | -1 | 3.9 | |
| Nov 14, 2024 | @ PHI | L | -8 | -5.9 | |
| Nov 24, 2024 | vs DAL | L | -8 | 11.3 | |
| Dec 1, 2024 | vs TEN | W | 23 | 10.5 | |
| Dec 15, 2024 | @ NO | W | 1 | 5.7 | |
| Dec 22, 2024 | vsPHI | W | 3 | -3.6 | |
| Dec 29, 2024 | vs ATL | W | 6 | 6.9 | |
| Jan 5, 2025 | @DAL | W | 4 | 7.0 | |
| Jan 12, 2025 | @ TB | W | 3 | -3.2 | |
| Jan 18, 2025 | @ DET | W | 14 | -9.9 | |
| Jan 26, 2025 | @PHI | L | -32 | -4.1 | |
| Sep 7, 2025 | vs NYG | W | 15 | -1.3 | |
| Sep 11, 2025 | @ GB | L | -9 | -6.9 | |
| Sep 21, 2025 | vs LV | W | 17 | 4.4 | |
| Sep 28, 2025 | @ATL | L | -7 | -4.1 | |
| Oct 5, 2025 | @ LAC | W | 17 | -9.3 | |
| Oct 13, 2025 | vs CHI | L | -1 | -3.6 | |
| Oct 19, 2025 | @DAL | L | -22 | -1.3 | |
| Oct 27, 2025 | @ KC | L | -21 | -6.4 | |
| Nov 2, 2025 | vs SEA | L | -24 | -13.2 | |
| Nov 9, 2025 | vsDET | L | -22 | -4.1 | |
| Nov 16, 2025 | vs MIA (neutral) | L | -3 | 0.5 | |
| Nov 30, 2025 | vs DEN | L | -1 | -5.8 | |
| Dec 7, 2025 | @ MIN | L | -31 | -4.3 | |
| Dec 14, 2025 | @NYG | W | 8 | -4.6 | |
| Dec 20, 2025 | vsPHI | L | -11 | -4.2 | |
| Dec 25, 2025 | vsDAL | L | -7 | 1.2 | |
| Jan 4, 2026 | @PHI | W | 7 | -9.8 | |
| Sep 13, 2026 | @PHI | L | -2 | 0.9 | |
| Sep 20, 2026 | @DAL | L | -17 | -0.0 | |
| Sep 27, 2026 | vsSEA | W | 2 | -3.8 | |
| Oct 4, 2026 | vs IND (neutral) | L | -17 | 2.1 | |
| Oct 11, 2026 | vsNYG | T | 0 | -0.8 | |
| Oct 19, 2026 | @ SF | L | -6 | -4.5 | |
| Nov 1, 2026 | vsPHI | W | 17 | -0.4 |
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 1.9 in 2024, plus 2.3 in 2025, plus 0.4 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 78% in 2024, 77% in 2025, 28% 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.
- Who played is read from the snap counts, which name every player who took a snap on offense, defense or special teams.