Edgehalla
Matthew Kessel headshotSt. Louis Blues logo

St. Louis Blues

Matthew Kessel

#51Defenseman6'3"214 lb

0.0 in 2 days
2025-26 regular season
29
GP
2
G
1
A
3
P
20
SOG
10.0% SH
12:32
TOI/GP

D · STL · NHL id 8482516

Matthew Kessel has played 29 games for the St. Louis Blues in 2025-26, scoring 2 goals and 1 assist (3 points) on 20 shots while averaging 12:32 a night (12:04 at even strength, 0:00 on the power play and 0:24 shorthanded). At 5v5 he has skated 41% of his 5v5 minutes with Tyler Tucker and 29% with Dalibor Dvorsky over the last 10 games, and the Blues have controlled 46% of shot attempts with Kessel on the ice (12-11 in goals, 63% offensive-zone starts). In the Blues' most recent game against PIT he was on D3 with Tyler Tucker and off the power play. He is shooting 10.0% this season against 4.4% across the 99 games in our data.

Right now

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

Pair
D3
Tyler Tucker
Power play
No PP unit
Penalty kill
No PK unit
Last 5: D3 · D3 · D2 · D3 · D3

Deployment timeline

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

Usage: 4 games, 14:32 average time on ice, PP1 in 0 games, 1 line changes.

PPLine32▲330m3m7m10m13m17m20mMar 6Mar 10Mar 13Mar 18Mar 24Mar 28Apr 1Apr 5Apr 9Apr 13
  • Even strength
  • Power play
  • Penalty kill
  • 5-game average
  • Did not play
  • ▲ promoted · ▼ demoted
4 games shown, 14:32 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 speed43rd4421.5 mph
Bursts 20+ mph45th4617
Hardest shot79th8095.2 mph
Offensive-zone time34th3540.7%
Distance skated29th2954.1 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 · 43 attempts, 20 on goal, 2 goals

Shot map, OPP at STL: 43 attempts, 20 on goal, 2 goals, 1.14 expected goals; best chance Matthew Kessel at 0.17 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 · 29 GP · 3 points vs 3.7 expected

Luck Meter →
Hold

Last 20 games: -6. Positive means running hot (sell), negative running cold (buy).

10.0%
102.0
25.0%
G vs xG
2 / 1.0
  • • Role rose over the last 10 games (TOI up 1:51 a game, 1 promotion event): some of the heat may be real.
Goals against expected goals
00.511.52+1.0goals above expected1.0σ10/184/14
  • Actual goals
  • Expected
  • ±1σ
  • Above expected
  • Below expected

Player analytics

Compare with another player →

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

  • Games played29
  • Goals2578th
  • Assists1701st
  • Points3686th
  • Power-play points0437th
  • Shorthanded points0227th
  • Shots on goal20688th
  • Hits22615th
  • Blocked shots26510th
  • Plus/minus+1283rd
  • Penalty minutes10608th
  • Faceoffs won0451st

Possession & shot quality (5-on-5 on-ice)

Transition, turnovers & faceoffs

Usage

Special teams & discipline

Luck & trend

NHL EDGE tracking

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 · 28 of 29 games through the sequence engine (more fill in as games are reprocessed)

MethodLeaders
−0.061
Season net
−0.35xG

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

MethodLeaders
Per 60
0.52
Attempts
3
0.029

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

MethodLeaders
Season
−0.20G
Per 60
−0.034
Drawn / taken
4 / 5minors

MethodLeaders
45.7%
43.6%
45.6%
Transition CF/60
4.0
Turnovers won/60
20.1
Turnovers lost/60
20.1

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

MethodLeaders
  • More of his shots than the league
  • Fewer
20 shots on goal, 2 goals, all situations
AreaHis shareLeagueG
Low Slot0%23%0
Center Point25%9%0
R Point15%6%0
L Circle5%13%0
L Point10%5%0
L Net Side0%3%0
R Net Side0%3%0

Role changes

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

All alerts →

How the goals happened

3 goals since 2023-24 with NHL EDGE tracking: press Replay to watch the tracking animation

Method
Goal anatomy
GamePlayEntryPassesShot mphNotesReplay
Nov 28, 2025 vs OTTReboundcarry025.0rebound
Nov 11, 2025 vs CGYRushloose3*83.3—
Apr 7, 2024 @ ANARushcarry2*66.1—

* includes a royal-road (cross-slot) pass. Derived from NHL EDGE puck and player tracking.

Linemates

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

TeammatePosGPShareCF% togetherGF% togetherCF% Kessel apartCF% mate apart
Tyler TuckerD21154:5345%48.8%44% (4-5)46.6% 92:3755.4% 78:53
Dalibor DvorskyRW2389:5626%47.7%50% (2-2)43.9% 196:0745.5% 179:20
Dylan HollowayLW2484:5525%49.6%57% (4-3)46.8% 196:2848.8% 260:19
Pius SuterC2279:5923%57.9%50% (3-3)44.3% 177:1847.7% 214:13
Jordan KyrouC2379:3823%50.0%38% (3-5)45.2% 198:3654.1% 215:31
Brayden SchennC2177:3022%43.0%40% (2-3)50.6% 174:2746.9% 215:44
Jimmy SnuggerudRW2474:4622%44.1%67% (4-2)46.6% 215:3243.3% 247:16
Pavel BuchnevichLW2362:0518%43.6%50% (2-2)44.5% 215:0044.9% 223:52
Nathan WalkerLW2060:3417%35.6%40% (2-3)48.5% 168:2842.7% 157:44
Alexey ToropchenkoRW2259:4817%39.8%40% (2-3)44.5% 219:3736.7% 171:00
Justin FaulkD755:0716%39.7%100% (1-0)52.3% 24:5445.0% 62:01
Oskar SundqvistC2055:0516%39.5%50% (2-2)45.0% 195:1236.2% 151:34
Jake NeighboursLW1951:5115%34.4%0% (0-2)47.0% 181:1346.2% 182:05
Mathieu JosephRW1550:0514%54.4%60% (3-2)46.6% 119:1038.5% 121:49

Linemate and opposition quality

2025-26 · 5v5 · 346:28 on ice · ranked against 270 defencemen

Quality of teammates (QoT)50.2%

55th percentile · higher = stronger linemates

Quality of competition (QoC)50.2%

72nd percentile · higher = tougher opponents

Faces tougher-than-usual opposition.

Each value is the ice-time-weighted average season xGF% of the skaters Kessel shared the 5v5 ice with, each shrunk toward 50%. Most skaters land between about 45% and 55% for QoT and 49% and 51% for QoC, so the percentile is the easier read.

Game log

29 games in 2025-26, newest first

DateOppResultGAP+/-PIMHITBLKEVPPPK
Apr 14vs PITW 7-5000-11024—12:5412:54——
Mar 26vs SJSW 2-1000-13022—13:0713:07——
Mar 8@ ANAW 4-000002221—18:2114:300:053:10
Mar 6@ SJSW 3-2000+10202—14:2114:21——
Mar 4@ SEAW 3-200000032—13:1011:11—1:59
Mar 1@ MINW 3-1000+11010—14:3114:31——
Feb 28vs NJDL 1-300002230—13:3913:39——
Feb 4@ DALL 4-5000+10001—7:497:49——
Jan 13vs CARW 3-000000023—16:0214:54—1:08
Jan 2vs VGKW 4-300000001—13:3713:37——
Dec 31@ COLL 1-601101023—16:0315:26—0:16
Dec 17vs WPGW 1-0000+11000—15:0313:39—1:24
Dec 6@ OTTW 2-100000000—8:458:37—0:08
Dec 1vs ANAL 1-400001000—12:4712:34——
Nov 29vs UTAW 1-000000001—13:2613:05—0:21
Nov 28vs OTTW 4-310101001—11:5811:58——
Nov 22@ NYIW 2-100000000—13:1112:31—0:40
Nov 20@ PHIOTL 2-3000-10000—10:169:29—0:47
Nov 18@ TOROTL 2-3000-11000—12:2311:39—0:44
Nov 15vs VGKL 1-4000-20003—14:2113:57—0:24

Season splits by strength

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

StrengthGPTOI/GPSAGFGAGF%
All situations29363:3412:3226532744.8%45.6%125154121152%11.114.059%
Even strength29349:4912:0426331245.7%46.4%124148121152%11.013.362%
5v529346:2811:5726330746.1%46.9%124144121152%11.013.163%
Power play10:050:0500——0000—0.00.0—
Penalty kill1211:380:5821016.7%25.0%1400—0.10.50%
4v443:210:50050.0%0.0%0400—0.00.250%
4v51211:380:5821016.7%25.0%1400—0.10.50%

Career by season

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

SeasonTeamGPGAP+/-PIMHITBLKTOI/GP
2025-26STL29213+1102010.0%222612:32
2024-25STL29033-310170.0%222313:08
2023-24STL39167012283.6%406516:48
2022-23STL2000-1030.0%0115:10

Matthew Kessel 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.