Edgehalla
Kyle Capobianco headshotDallas Stars logo

Dallas Stars

Kyle Capobianco

#20Defenseman6'3"192 lb

0.0 in 3 days
2025-26 regular season
33
GP
2
G
3
A
5
P
18
SOG
11.1% SH
12:08
TOI/GP

D · DAL · NHL id 8478476

Kyle Capobianco has played 33 games for the Dallas Stars in 2025-26, scoring 2 goals and 3 assists (5 points) on 18 shots while averaging 12:08 a night (11:42 at even strength, 0:24 on the power play and 0:01 shorthanded). At 5v5 he has skated 46% of his 5v5 minutes with Alexander Petrovic and 30% with Mavrik Bourque over the last 10 games, and the Stars have controlled 49% of shot attempts with Capobianco on the ice (19-17 in goals, 61% offensive-zone starts). In the Stars' most recent game against TOR he was on D3 with Alexander Petrovic and on PP2; added to PP2 in the last game. He is shooting 11.1% this season against 8.0% across the 108 games in our data.

Right now

From the Apr 13 game vs TOR, detected from shift data

Pair
D3
Alexander Petrovic
Power play
PP2
Mikko RantanenJason RobertsonMavrik BourqueJustin Hryckowian
Penalty kill
No PK unit
Added to PP2 in the last gameLast 5: D3 · D3 · D2 · D3 · D3/PP2

Deployment timeline

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

Usage: 2 games, 11:23 average time on ice, PP1 in 0 games, 0 line changes.

PPLine330m3m7m10m13m17mMar 6Mar 10Mar 14Mar 18Mar 22Mar 26Mar 29Apr 2Apr 7Apr 11
  • Even strength
  • Power play
  • Penalty kill
  • 5-game average
  • Did not play
  • ▲ promoted · ▼ demoted
2 games shown, 11:23 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 speed25th2520.9 mph
Bursts 20+ mph39th4014
Hardest shot61st6292.5 mph
Offensive-zone time91st9144.9%
Distance skated30th3160.0 mi
High-danger SOG1st00
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 · 66 attempts, 18 on goal, 2 goals

Shot map, OPP at DAL: 66 attempts, 18 on goal, 2 goals, 1.17 expected goals; best chance Kyle Capobianco at 0.23 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 · 33 GP · 5 points vs 6.0 expected

Luck Meter →
Hold

Last 20 games: -21. Positive means running hot (sell), negative running cold (buy).

11.1%
101.6
26.3%
G vs xG
2 / 1.2
Goals against expected goals
00.511.52+0.8goals above expected0.7σ10/284/13
  • 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 played33
  • Goals2578th
  • Assists3651st
  • Points5655th
  • Power-play points0437th
  • Shorthanded points0227th
  • Shots on goal18692nd
  • Hits12677th
  • Blocked shots27493rd
  • Plus/minus+1283rd
  • Penalty minutes8640th
  • 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 · 31 of 33 games through the sequence engine (more fill in as games are reprocessed)

MethodLeaders
−0.035
Season net
−0.23xG

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

MethodLeaders
Per 60
0.31
Attempts
2
0.001

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

MethodLeaders
Season
−0.20G
Per 60
−0.031
Drawn / taken
3 / 4minors

MethodLeaders
52.9%
52.3%
52.3%
Transition CF/60
3.1
Turnovers won/60
22.8
Turnovers lost/60
19.4

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

MethodLeaders
  • More of his shots than the league
  • Fewer
18 shots on goal, 2 goals, all situations
AreaHis shareLeagueG
L Point39%5%0
Low Slot0%23%0
Center Point17%9%1
Outside L0%4%0
L Circle17%13%0
L Net Side0%3%0
R Net Side0%3%0

How the goals happened

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

Method
Goal anatomy
GamePlayEntryPassesShot mphNotesReplay
Jan 10, 2026 @ SJSOdd-man rushcarry064.72-on-1
Dec 2, 2025 @ NYRForecheck turnover—070.4—

* 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 Capobianco

TeammatePosGPShareCF% togetherGF% togetherCF% Capobianco apartCF% mate apart
Alexander PetrovicD22133:4335%47.6%69% (9-4)49.4% 131:4441.3% 207:29
Justin HryckowianC31111:1929%48.6%14% (1-6)49.8% 254:2143.9% 236:55
Mavrik BourqueC31111:0729%56.8%55% (6-5)46.0% 262:1549.0% 290:54
Jason RobertsonLW3297:1625%49.5%67% (10-5)49.1% 282:2251.2% 377:09
Oskar BäckC3196:5025%54.7%33% (2-4)47.9% 275:1245.6% 216:23
Radek FaksaC3089:4723%55.8%50% (1-1)47.9% 266:1744.6% 195:00
Wyatt JohnstonC2989:4123%42.8%63% (5-3)53.8% 255:5747.3% 342:50
Mikko RantanenRW3086:2522%41.6%71% (5-2)52.7% 262:1247.3% 360:02
Sam SteelC2883:5622%50.0%83% (5-1)49.7% 241:5245.1% 286:18
Jamie BennLW2577:4420%45.5%43% (3-4)50.4% 229:2041.7% 211:23
Matt DucheneC1967:3518%39.6%36% (4-7)54.2% 157:0440.4% 191:27
Roope HintzLW2566:2717%51.9%73% (8-3)47.8% 243:4950.8% 252:04
Ilya LyubushkinD1363:0816%41.7%33% (2-4)48.5% 86:2038.4% 112:38
Colin BlackwellC2061:3316%57.6%0% (0-4)48.3% 179:5046.7% 123:43

Linemate and opposition quality

2025-26 · 5v5 · 384 min on ice · ranked against 270 defencemen

51.4%

76th percentile · higher = stronger linemates

49.0%

5th percentile · higher = tougher opponents

Favourable spot: strong linemates against weaker opponents.

Each value is the ice-time-weighted average season xGF% of the skaters Capobianco shared the 5v5 ice with. Small samples lean on each skater's previous season (or 50% for newcomers). 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

33 games in 2025-26, newest first

DateOppResultGAP+/-PIMHITBLKEVPPPK
Apr 13@ TORW 6-5000+11000—14:5714:120:45—
Apr 2vs WPGW 3-000000001—7:497:49——
Feb 4vs STLW 5-4000-10011—14:1714:17——
Feb 2vs WPGW 4-300001001—12:2812:24—0:04
Jan 31@ UTAW 3-2000+11011—12:0012:00——
Jan 29@ VGKW 5-4000+21002—12:2012:19—0:01
Jan 27@ STLW 4-3000-20002—10:2510:04—0:12
Jan 23vs STLW 3-200000001—10:5010:50——
Jan 18vs TBLL 1-4000-10000—12:2312:23——
Jan 15@ UTAL 1-200001201—12:2911:540:35—
Jan 13@ ANAL 1-3000-20022—12:5612:240:19—
Jan 12@ LAKW 3-100000001—12:3112:31——
Jan 10@ SJSOTL 4-5101+11001—10:3810:38——
Jan 7@ WSHW 4-1000+10011—10:1410:14——
Dec 27vs CHIOTL 3-4000+11210—12:3412:260:08—
Dec 13vs FLAL 0-4000-11001—12:5412:54——
Dec 11@ MINL 2-500000000—12:0412:04——
Dec 9@ WPGW 4-3000-20002—9:529:52——
Dec 7vs PITW 3-2000-10002—14:3014:110:19—
Dec 5vs SJSW 4-1000+11022—16:1615:200:56—

Season splits by strength

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

StrengthGPTOI/GPSAGFGAGF%
All situations33400:2412:0835635450.1%51.0%170170191851%18.816.262%
Even strength33386:0611:4233735049.1%50.0%162167191753%17.316.162%
5v533384:2011:3933534749.1%50.1%161167191753%17.215.761%
Power play1413:130:5715383.3%85.7%7200—1.20.067%
Penalty kill40:180:0500——0000—0.00.0—
5v41413:010:5615383.3%85.7%7200—1.20.0100%

Career by season

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

SeasonTeamGPGAP+/-PIMHITBLKTOI/GP
2025-26DAL33235+181811.1%122712:08
2024-25DAL1000-240—1011:23
2022-23PlayoffsWPG1000-1010.0%1213:02
2022-23WPG14202+161414.3%12612:20
2021-22ARI45279-1238405.0%434616:00
2020-21ARI2000-2230.0%1214:28
2019-20ARI9101-121010.0%141014:46
2018-19ARI2000-2010.0%2216:05
2017-18ARI1000-100—3113:33

Kyle Capobianco 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.