Edgehalla
Logan Mailloux headshotSt. Louis Blues logo

St. Louis Blues

Logan Mailloux

#23Defenseman6'3"209 lb

0.0 in 2 days
2025-26 regular season
67
GP
5
G
8
A
13
P
81
SOG
6.2% SH
16:46
TOI/GP

D · STL · NHL id 8482733

Logan Mailloux has played 67 games for the St. Louis Blues in 2025-26, scoring 5 goals and 8 assists (13 points) on 81 shots while averaging 16:46 a night (15:08 at even strength, 0:37 on the power play and 0:39 shorthanded). At 5v5 he has skated 88% of his 5v5 minutes with Philip Broberg and 29% with Jordan Kyrou over the last 10 games, and the Blues have controlled 48% of shot attempts with Mailloux on the ice (33-48 in goals, 57% offensive-zone starts). In the Blues' most recent game against UTA he was on D1 with Philip Broberg and on PP2; moved up to D1 (from D2) in the last game. He is shooting 6.2% this season against 7.5% across the 75 games in our data.

Right now

From the Apr 16 game vs UTA, detected from shift data

Moved up to D1 (from D2) in the last gameLast 5: D2/PP2 · D2 · D1/PP1 · D2/PP2 · D1/PP2

Deployment timeline

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

Usage: 20 games, 20:42 average time on ice, PP1 in 4 games, 14 line changes.

PPLine21▲2▼2▲1▲1▼3▲3▼2▲3▼2▲23▼2▲3▼2▲2▼1▲2▼1▲0m8m17m25m33mMar 8Mar 12Mar 15Mar 21Mar 26Mar 30Apr 3Apr 7Apr 11Apr 14
  • Even strength
  • Power play
  • Penalty kill
  • 5-game average
  • Did not play
  • ▲ promoted · ▼ demoted
20 games shown, 20:42 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 speed60th6021.9 mph
Bursts 20+ mph79th7951
Hardest shot77th7894.9 mph
Offensive-zone time55th5541.8%
Distance skated55th56167.1 mi
High-danger SOG70th716
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 · 189 attempts, 81 on goal, 5 goals

Shot map, OPP at STL: 189 attempts, 81 on goal, 5 goals, 4.26 expected goals; best chance Logan Mailloux at 0.54 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 · 67 GP · 13 points vs 17.2 expected

Luck Meter →
Hold

Last 20 games: +34. Positive means running hot (sell), negative running cold (buy).

6.2%
97.7
29.5%
G vs xG
5 / 4.4
  • • Role rose over the last 10 games (TOI up 4:50 a game, PP share 8% → 29%, 4 promotion events): some of the heat may be real.
Goals against expected goals
0246+0.6goals above expected0.3σ10/94/16
  • 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

  • Games played67
  • Goals5443rd
  • Assists8513th
  • Points13517th
  • Power-play points1380th
  • Shorthanded points0227th
  • Shots on goal81386th
  • Hits93199th
  • Blocked shots56218th
  • Plus/minus−10561st
  • Penalty minutes48117th
  • 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 · 66 of 67 games through the sequence engine (more fill in as games are reprocessed)

MethodLeaders
−0.075
Season net
−1.26xG

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

MethodLeaders
Per 60
0.42
Attempts
7
0.001

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

MethodLeaders
Season
−1.22G
Per 60
−0.065
Drawn / taken
18 / 24minors

MethodLeaders
48.0%
45.2%
48.1%
Transition CF/60
4.1
Turnovers won/60
20.7
Turnovers lost/60
21.7

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

MethodLeaders
  • More of his shots than the league
  • Fewer
81 shots on goal, 5 goals, all situations
AreaHis shareLeagueG
R Point31%6%0
Low Slot6%23%1
L Circle4%13%1
Outside R10%4%1
Center Point12%9%1
High Slot4%7%0
R Circle15%12%0

Role changes

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

All alerts →

How his goals happened

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

Method
Goal anatomy
GamePlayEntryPassesShot mphNotesReplay
Apr 16, 2026 @ UTAForecheck turnovercarry046.13-on-1
Apr 14, 2026 vs PITPoint shotcarry276.5—
Mar 4, 2026 @ SEAReboundcarry06.8rebound
Mar 1, 2026 @ MINOdd-man rushcarry075.03-on-2
Dec 12, 2025 vs CHIRushcarry085.1—
Feb 5, 2025 @ LAKRushcarry173.8—
Oct 19, 2024 @ NYIReboundcarry159.23-on-2, rebound

* 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 Mailloux

TeammatePosGPShareCF% togetherGF% togetherCF% Mailloux apartCF% mate apart
Cam FowlerD46441:2444%47.9%33% (11-22)47.9% 237:2648.5% 347:30
Philip BrobergD35354:2335%48.0%55% (17-14)50.6% 196:3948.5% 274:58
Dalibor DvorskyRW59250:5625%48.7%40% (6-9)48.3% 643:4246.7% 462:17
Jimmy SnuggerudRW52244:2124%46.6%50% (11-11)48.8% 559:0950.3% 484:25
Dylan HollowayLW46232:1523%44.4%46% (12-14)48.7% 476:3854.1% 436:39
Pavel BuchnevichLW60219:2122%53.2%37% (7-12)47.1% 689:4850.4% 548:44
Jordan KyrouC53216:2622%53.3%43% (9-12)47.3% 600:0554.9% 468:58
Pius SuterC49200:4020%48.1%55% (6-5)47.5% 553:3448.6% 400:14
Jake NeighboursLW57197:1420%46.1%47% (8-9)49.1% 671:1051.6% 524:07
Brayden SchennC45188:0119%52.1%47% (8-9)48.3% 444:4046.5% 429:51
Robert ThomasC45176:1918%50.9%50% (11-11)47.1% 514:1053.7% 463:22
Alexey ToropchenkoRW52162:1816%42.2%20% (2-8)51.0% 641:4344.3% 353:01
Jonatan BerggrenRW34152:3715%57.2%33% (4-8)45.0% 377:2552.6% 283:34
Oskar SundqvistC41125:1913%38.4%33% (4-8)49.0% 471:0540.1% 282:59

Game log

67 games in 2025-26, newest first

DateOppResultGAP+/-PIMHITBLKEVPPPK
Apr 16@ UTAW 5-3101+32011—22:3420:210:44—
Apr 14vs PITW 7-5112+14001—21:2717:210:551:11
Apr 13vs MINW 6-3000+31030—24:1715:094:482:59
Apr 11@ CHIW 5-301101010—20:2616:490:181:50
Apr 9vs WPGL 2-3000-10021—20:1316:072:230:52
Apr 7vs COLL 1-3000-23210—20:0415:491:09—
Apr 5@ COLW 3-2000+21030—19:4715:031:592:22
Apr 3@ ANAW 6-2000+11230—19:1114:461:522:28
Apr 1@ LAKOTL 1-2000+12210—21:0119:171:260:18
Mar 30@ SJSL 4-5000-20004—19:5017:330:381:39
Mar 28vs TORW 5-1000+14021—19:5916:000:483:05
Mar 26vs SJSW 2-100002545—20:4918:420:541:09
Mar 24vs WSHW 3-0011+21012—20:5115:112:212:15
Mar 21@ VANW 3-1022+11010—21:5916:243:062:01
Mar 18@ CGYOTL 1-200002024—26:5622:100:493:57
Mar 15@ WPGL 2-301102001—24:5817:321:073:24
Mar 13vs EDMW 3-2000-11420—21:1619:530:450:38
Mar 12@ CARW 3-1000+10020—21:4117:340:202:47
Mar 10vs NYIOTL 3-4000-11011—23:3919:391:571:42
Mar 8@ ANAW 4-0000+13002—20:1613:272:233:49

Season splits by strength

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

StrengthGPTOI/GPSAGFGAGF%
All situations671123:3316:46936104447.3%45.7%424495445744%51.055.652%
Even strength671013:5315:0886292648.2%46.6%386443334940%40.744.557%
5v5671001:5314:5785291448.2%46.7%382437334841%40.143.257%
Power play3341:141:1532488.9%85.7%1431150%1.90.488%
Penalty kill3144:001:2597211.1%11.9%7331517%0.45.60%
4v4109:140:558466.7%62.5%2100—0.40.343%
3v3 (OT)32:460:552820.0%25.0%25010%0.21.0100%
5v43341:141:1532488.9%85.7%1431150%1.90.488%
4v53142:251:2296711.8%12.7%7291517%0.45.20%
6v5, own net empty149:240:4021970.0%70.0%1113175%1.92.8100%
5v6, opponent net empty2011:350:3592725.0%33.3%595183%5.01.90%

Career by season

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

SeasonTeamGPGAP+/-PIMHITBLKTOI/GP
2025-26STL675813-1048816.2%935616:46
2024-25MTL7224-561020.0%9816:12
2023-24MTL1011+1020.0%1121:14

Logan Mailloux 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.