Net Goals 101 · component 9 of 11
Faceoffs
The faceoffs component counts the draws a player wins and loses and prices each net win by what it is worth on the scoreboard. This page works one real season through from the raw events to the number on the card. Every figure is recomputed from the model’s own data and checked against the published value.
Step 01 · Count
580 won, 392 lost
Every faceoff of 2025-26, in all three zones and at every strength, is a win for one centre and a loss for the other. Matthews took 972: 59.7%.
| Zone (his end) | Won | Lost | Win % | Net |
|---|---|---|---|---|
| Offensive zone | 201 | 125 | 61.7% | +76 |
| Neutral zone | 183 | 118 | 60.8% | +65 |
| Defensive zone | 196 | 149 | 56.8% | +47 |
| All | 580 | 392 | 59.7% | +188 |
His most frequent opponents:
| Opponent | Won | Lost | Net |
|---|---|---|---|
| Sidney Crosby | 22 | 25 | −3 |
| Dylan Larkin | 18 | 18 | +0 |
| Nick Suzuki | 21 | 12 | +9 |
| Mika Zibanejad | 17 | 8 | +9 |
| Justin Sourdif | 12 | 11 | +1 |
Step 02 · Price
What a faceoff win is worth
A net faceoff win is worth about 0.010 goals. The estimate compares the same team with itself: within each team-season, does it win by more on nights it wins more draws? A fixed-effects regression of final goal margin on net faceoff wins over 12,396 team-games (2021-22 on) gives +0.0100 goals each (t = 3.6).
This is the one component that overlaps the others: possession after a draw is already in the on-ice flow of everyone on the ice, so this column double-counts a little on purpose, to show a real, very stable skill. It is small. The most net wins in 2025-26, as season totals (500+ draws; the card is per game, so a full season of +200 can rank below a shorter one):
| Centre | Net wins | Win % | Goals |
|---|---|---|---|
| Jonathan Toews | +248 | 62.1% | +2.48 |
| Dylan Strome | +220 | 58.2% | +2.20 |
| John Tavares | +210 | 57.5% | +2.10 |
| Claude Giroux | +209 | 63.1% | +2.09 |
| Nico Hischier | +208 | 55.8% | +2.08 |
Step 03 · Position
Measured against the average forward
After every other step, each component is re-centred once more, separately for forwards and for defencemen, so the average forward in 2025-26 is exactly zero in every column. The games-weighted mean faceoff value of all forwards that season was +0.00004 net goals per game, so 60 games of it come off:
Step 04 · Result
Per 84 games
Ratings are quoted per 84 games, one full schedule, so a part season and a full one sit on the same scale.
Recomputed +2.63; his 2025-26 row on the player card and the Players table shows +2.6. They match.
Step 05 · Context
How unusual is this?
| Percentile | 5th | 25th | Median | 75th | 95th | Best |
|---|---|---|---|---|---|---|
| Faceoffs NG/84 | −0.7 | −0.1 | +0.0 | +0.0 | +1.0 | +2.6 |
Skaters with 40 or more games in 2025-26 (612 players). Auston Matthews ranks 1 of 612.
How much of a season like this is skill? The model estimates, from how much players’ own rates bounce between seasons versus how much players differ, that a career rate of faceoff value is half signal and half noise after 44 games. Season rows like this one are shown exactly as they happened; careers and the card’s Regressed view are pulled toward average by that amount.
The numbers on this page were rebuilt on 2026-10-08 from the same files the cards are built from. The model behind every step is described on Net Goals 101; definitions are in the Reference.