Draw Duel
Matthew Wood faceoff stats, 2025-26
NSH · R · Right shot · full player page
Model rating
39.1%
90%: 34.9%–43.5% vs an average regular, on 226 draws since 2023-24
2025-26 FO%
39.8%
82 won of 206 (regular season)
Strong / weak side
39.1% / 52.8%
138 strong-side, 36 weak-side draws this season
Next game
2.9 FOW
2026-10-06 vs TOR: 8 draws at 35.2%, range 0–5
Where Wood wins draws
Win % at every dot, 2025-26 regular season, in his own attacking direction.
Show as a table
| Dot | Draws | Won | FO% |
|---|---|---|---|
| OZ left | 18 | 9 | 50.0% |
| OZ right | 77 | 35 | 45.5% |
| NZ left (att.) | 8 | 5 | 62.5% |
| NZ right (att.) | 9 | 4 | 44.4% |
| Centre | 32 | 9 | 28.1% |
| NZ left (def.) | 7 | 3 | 42.9% |
| NZ right (def.) | 8 | 5 | 62.5% |
| DZ left | 3 | 2 | 66.7% |
| DZ right | 44 | 10 | 22.7% |
Toughest and easiest opponents
Model win % against today's regular centres, averaged over home and road and every dot. This is a prediction, not his record.
Toughest
- Claude Giroux OTT · R31.4%
- Aatu Räty VAN · L31.6%
- Jean-Gabriel Pageau NYI · R32.2%
- J.T. Miller NYR · L32.5%
- Auston Matthews TOR · L32.7%
- Vincent Trocheck UTA · R32.7%
Easiest
- Jack Hughes NJD · L52.1%
- Noah Ostlund BUF · L51.7%
- Trevor Zegras PHI · L50.6%
- Danila Yurov MIN · L48.8%
- Pavel Buchnevich STL · L48.5%
- Calum Ritchie NYI · R48.4%
Splits by season
| Season | All | EV | PP | PK | OZ | NZ | DZ | Strong | Weak |
|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | 35.3% 17 | 42.9% 14 | — 0 | 0.0% 3 | 50.0% 8 | 0.0% 3 | 33.3% 6 | 30.8% 13 | 66.7% 3 |
| 2025-26 | 39.8% 206 | 39.8% 191 | 40.0% 15 | — 0 | 46.3% 95 | 40.6% 64 | 25.5% 47 | 39.1% 138 | 52.8% 36 |
| 2024-25 | 33.3% 3 | 33.3% 3 | — 0 | — 0 | 0.0% 1 | — 0 | 50.0% 2 | 33.3% 3 | — 0 |
Small numbers are draws taken. Strong = his strong-side dots (a left shot's left dots, in his own attacking direction); centre-ice draws count in neither.
Head-to-head, last three seasons
Raw records against his most frequent opponents next to what the model expected at the dots they actually met at. The blended number moves the model toward the record by n / (n + 500), because pair-specific edges are tiny (about ±2 points) and most of a lopsided record is luck.
| Opponent | Record | Raw | Model | Blended | Unusual? |
|---|---|---|---|---|---|
| Michael Misa | 8–4 | 66.7% | 43.5% | 44.1% | a bit unusual (z 1.6) |
| Scott Laughton | 6–6 | 50.0% | 35.4% | 35.8% | a bit unusual (z 1.1) |
| Ryan Poehling | 2–8 | 20.0% | 38.0% | 37.6% | a bit unusual (z -1.2) |
| Sean Monahan | 2–7 | 22.2% | 38.0% | 37.7% | normal luck (z -1.0) |
| Chandler Stephenson | 5–4 | 55.6% | 36.3% | 36.7% | a bit unusual (z 1.2) |
| Adam Lowry | 3–5 | 37.5% | 34.7% | 34.7% | normal luck (z 0.2) |
| Jason Dickinson | 3–4 | 42.9% | 36.8% | 36.9% | normal luck (z 0.3) |
| Phillip Danault | 2–4 | 33.3% | 34.4% | 34.4% | normal luck (z -0.1) |
| Fraser Minten | 2–2 | 50.0% | 40.3% | 40.3% | normal luck (z 0.4) |
| Shane Wright | 1–3 | 25.0% | 46.1% | 45.9% | normal luck (z -0.8) |
| Zack Ostapchuk | 1–3 | 25.0% | 40.7% | 40.6% | normal luck (z -0.6) |
| Tomas Hertl | 0–4 | 0.0% | 33.9% | 33.6% | a bit unusual (z -1.4) |
Last 10 games
| Date | Opp | FOW | Draws | FO% |
|---|---|---|---|---|
| 2026-10-03 | vs DAL | 5 | 9 | 55.6% |
| 2026-10-01 | vs MIN | 1 | 8 | 12.5% |
| 2026-04-16 | vs ANA | 1 | 6 | 16.7% |
| 2026-04-13 | vs SJS | 2 | 6 | 33.3% |
| 2026-04-09 | @ UTA | 1 | 5 | 20.0% |
| 2026-04-07 | @ ANA | 3 | 11 | 27.3% |
| 2026-04-06 | @ LAK | 5 | 9 | 55.6% |
| 2026-04-04 | @ SJS | 6 | 12 | 50.0% |
| 2026-04-02 | @ LAK | 3 | 8 | 37.5% |
| 2026-03-29 | @ TBL | 0 | 1 | 0.0% |
Projected faceoffs won
- 2026-10-06 vs TOR likely opponents: John Tavares (33%), Auston Matthews (32%)2.9 FOW 0–5
- 2026-10-08 vs MTL likely opponents: Nick Suzuki (39%), Phillip Danault (35%)3.2 FOW 1–6
- 2026-10-10 vs OTT likely opponents: Claude Giroux (34%), Lars Eller (37%)3.2 FOW 1–6
FAQ
What is Matthew Wood's faceoff percentage?
The season line above shows Matthew Wood's raw faceoff wins and percentage this season. The model rating beside it is his expected win rate against an average regular centre at a neutral dot, adjusted for opponents, home ice and dot side, with a 90% interval.
How many faceoffs will Matthew Wood win tonight?
When Matthew Wood has a game scheduled, the projection above gives expected draws, expected win rate against tonight's likely opposing centres, and a 10th–90th percentile range of faceoffs won. Projections update nightly.
Is Matthew Wood better on his strong side?
Almost every centre is. The strong/weak split above compares his win rate on his strong-side dots (a left shot's left dots) with his weak-side dots. League-wide, strong-side takers win about 52.6% and weak-side takers about 44.9%.