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Adam Engstrom headshotMontreal Canadiens logo

Montreal Canadiens

Adam Engstrom

#42Defenseman6'2"192 lb

0.0 in 2 days
2025-26 regular season
15
GP
0
G
1
A
1
P
11
SOG
0.0% SH
13:03
TOI/GP

D · MTL · NHL id 8483686

Adam Engstrom has played 15 games for the Montreal Canadiens in 2025-26, scoring 0 goals and 1 assist (1 points) on 11 shots while averaging 13:03 a night (12:38 at even strength, 0:14 on the power play and 0:05 shorthanded). At 5v5 he has skated 61% of his 5v5 minutes with Arber Xhekaj and 28% with Oliver Kapanen over the last 10 games, and the Canadiens have controlled 51% of shot attempts with Engstrom on the ice (8-6 in goals, 69% offensive-zone starts). In the Canadiens' most recent game against PHI he was on D2 with Kaiden Guhle and on PP2; added to PP2 in the last game. He is shooting 0.0% this season.

Right now

From the Apr 14 game vs PHI, detected from shift data

Added to PP2 in the last gameLast 5: D3 · D3 · D3 · D2/PP2 · D3/PP2

Deployment timeline

2025-26 · per-game ice time by strength, with line and power-play unit changes

Usage: 4 games, 14:15 average time on ice, PP1 in 0 games, 1 line changes.

PPLine332▲30m3m7m10m13m17m20mMar 10Mar 14Mar 17Mar 21Mar 26Mar 29Apr 2Apr 5Apr 9Apr 12
  • Even strength
  • Power play
  • Penalty kill
  • 5-game average
  • Did not play
  • ▲ promoted · ▼ demoted
4 games shown, 14:15 average. Line and PP unit come from where the player's ice time ranks among his teammates that night.

NHL EDGE tracking

2025-26 percentiles among skaters at his position

Source: NHL EDGE
Top speed35th3621.3 mph
Bursts 20+ mph27th287
Hardest shot30th3086.8 mph
Offensive-zone time76th7643.4%
Distance skated22nd2328.3 mi
High-danger SOG29th301
Percentile among position peers│ tick = 3-season weighted

Season-level NHL EDGE puck and player tracking, refreshed nightly. The percentile is the league rank among skaters this season; the label at the right is the raw value.

Shot map

2025-26 · 29 attempts, 11 on goal, 0 goals

Shot map, OPP at MTL: 29 attempts, 11 on goal, 0 goals, 0.64 expected goals; best chance Adam Engstrom at 0.14 xG.

  • Even strength
  • Power play
  • Penalty kill
  • Goal
  • Shot on goal
  • Missed
  • Blocked
Every attempt (goals, shots, misses and blocks), attacking toward the right (or the top on phones).

Luck

2025-26 · 15 GP · 1 points vs 2.9 expected

Luck Meter →
Hold

Last 20 games: -31. Positive means running hot (sell), negative running cold (buy).

0.0%
104.1
11.1%
G vs xG
0 / 0.6
  • • Role rose over the last 10 games (TOI up 1:43 a game, PP share 0% → 5%, 5 promotion events): some of the heat may be real.
Goals against expected goals
00.51-0.6goals below expected-0.8σ11/264/14
  • Actual goals
  • Expected
  • ±1σ
  • Above expected
  • Below expected

2025-26 regular season. Rank is among all qualified players; the bar is his percentile among defencemen. Each stat links to its explainer.

Fantasy box score

Usage

Special teams & discipline

Luck & trend

Unranked rows are below the sample minimum (20 GP, 200 five-on-five minutes, 100 draws or 10 goalie games).

Beyond the box score

2025-26 regular season · 15 of 15 games through the sequence engine

MethodLeaders
−0.042
Season net
−0.13xG

5-on-5. Each takeaway is credited, and each giveaway charged, at the league xG value of the zone.

MethodLeaders
Per 60
0.00
Attempts
0
0.000

5-on-5 shots within 10 seconds of winning the puck outside the offensive zone.

MethodLeaders
Season
−0.61G
Per 60
−0.187
Drawn / taken
1 / 4minors

MethodLeaders
51.5%
53.8%
51.4%
Transition CF/60
4.1
Turnovers won/60
19.7
Turnovers lost/60
19.4

5-on-5 while he is on the ice.

Role changes

Notable promotions, demotions and ice-time swings from Line Watch

All alerts →

Linemates

2025-26 · 5v5 time together and how each pairing performs with and without Engstrom

TeammatePosGPShareCF% togetherGF% togetherCF% Engstrom apartCF% mate apart
Arber XhekajD1186:2846%50.3%33% (2-4)58.4% 54:1345.9% 55:55
Oliver KapanenC1552:2528%52.9%83% (5-1)50.4% 136:0739.4% 125:01
Ivan DemidovRW1348:1626%47.1%83% (5-1)51.0% 116:3241.1% 105:11
Joseph VelenoC1447:5825%51.8%50% (2-2)49.0% 125:0045.2% 94:02
Josh AndersonRW1247:4225%50.0%50% (1-1)52.7% 104:5946.7% 87:43
Brendan GallagherRW1246:1325%56.8%67% (2-1)48.5% 102:5440.8% 80:16
Juraj SlafkovskýLW1345:1324%48.9%71% (5-2)50.2% 122:5643.5% 128:41
Alexandre TexierC1444:4724%46.1%67% (2-1)53.0% 133:0353.8% 130:35
Jake EvansC1034:4118%41.3%33% (2-4)56.1% 96:1048.0% 81:32
Owen BeckC733:3818%55.4%— (0-0)48.2% 54:3053.5% 35:11
Zachary BolducC931:4117%41.5%0% (0-3)58.2% 87:3151.0% 82:44
Lane HutsonD1029:5216%50.0%67% (2-1)52.7% 101:4454.8% 161:20
Cole CaufieldRW1026:2414%52.3%— (0-0)52.8% 107:4056.8% 105:52
Nick SuzukiC1026:1614%55.3%0% (0-1)52.0% 107:4859.0% 116:19

Game log

15 games in 2025-26, newest first

DateOppResultGAP+/-PIMHITBLKEVPPPK
Apr 14@ PHIL 2-4000-11010—15:2812:392:24—
Apr 11vs CBJL 2-500001002—17:2115:261:050:50
Apr 9vs TBLW 2-100001011—9:128:59—0:03
Apr 7vs FLAW 4-301101210—15:5015:34——
Jan 1@ CARW 7-5000+21002—13:0413:04——
Dec 30@ FLAW 3-200000200—11:2911:24——
Dec 21@ PITOTL 3-4000+10200—10:4010:40——
Dec 20vs PITW 4-000002000—11:1211:12——
Dec 18vs CHIW 4-100002010—16:1316:13——
Dec 16vs PHIL 1-4000-10001—15:4515:07—0:26
Dec 14vs EDMW 4-1000+10000—12:3612:19——
Dec 13@ NYROTL 4-500000020—11:1611:16——
Dec 11@ PITW 4-200000200—11:3011:21——
Nov 29@ COLL 2-700001012—13:2913:29——
Nov 26@ UTAW 4-300001000—10:4210:42——

Season splits by strength

2025-26 regular season · on-ice numbers from shift and play-by-play data

StrengthGPTOI/GPSAGFGAGF%
All situations15195:4713:0316716350.6%49.4%69829756%8.49.171%
Even strength15189:2512:3816315651.1%50.4%68788657%8.17.767%
5v515188:3212:3416315651.1%50.4%68788657%8.17.769%
Power play23:291:4530100.0%—0000—0.00.0100%
Penalty kill31:190:26020.0%0.0%0200—0.00.2—
5v423:291:4530100.0%—0000—0.00.0100%

Career by season

Seasons in Edgehalla's data (2025-26 is being backfilled; earlier seasons follow)

SeasonTeamGPGAP+/-PIMHITBLKTOI/GP
2025-26MTL15011+28110.0%7813:03

Adam Engstrom news

Headlines via LineupExperts. Links open the original publisher.

On-ice and deployment numbers are derived by Edgehalla from NHL play-by-play and shift data. Tracking percentiles are from NHL EDGE. Data updates after every game.