Returning regular · 2025-26

Esa Lindell

Dallas Stars · LD · L shot · age 32 at the dated snapshot.

Team: DAL
Lane: LD
Age: 32

Production and deployment

How the points were built

Official NHL 2025–26 regular-season reports. A missing split stays “—”; it is never converted to zero.

Games82

Goals6

Assists26

Points32

Even strength28all even-strength points

Power play2

Short handed2

Empty net3

5v5 points / 600.958

Average TOI23:14

PP TOI0:45

PK TOI3:56

Organizational context

5 LD regulars in DAL

The all-team median is 4. DAL’s farm system ranks #31 in the maintained two-board consensus.

Thin lane

Questions a GM still has to answer

How much of the scoring comes at five-on-five, on special teams, or into an empty net?
Is the player creating the play, finishing it, or receiving a secondary point?
Does deployment reveal trust, scarcity, underuse, or a role the roster cannot offer?
What contract, acquisition cost, development alternative and Cup-window effect complete the argument?

Shot quality · 2025-26

Expected goals

CapOrCup's shot model (distance, angle, shot type, strength, rebounds, rushes), trained on 2023-24 and 2024-25 and tested on unseen games (AUC 0.756). Finishing is goals minus expected goals; it is noisy in one season.

Unblocked shots124

Expected goals7.66.1% per shot

Goals6

Finishing−1.6goals above expected

CapOrCup measures · 2025-26

What happens while he plays

Measured from the league's play-by-play and shift charts, not from the scoresheet. Expected goals are counted for every player on the ice, and a goal is credited to whoever was on the ice when the sequence began, including players who had changed off before it was scored.

Share of chance quality47%2.88 expected goals for and 3.31 against per 60 minutes

Drive, three seasons (ranking measure)+2.5 pts5v5 chance share against his club without him, over this season and the two before (weights 1 / 0.7 / 0.4; 1438 / 1366 / 1327 minutes) · 80% band 0.6 to 4.3 pts. This is the number the rankings order by: it predicts next season better than one season does.

Drive, this season only+5 ptsat 5-on-5, over 24 hours: his share minus the club's share when he is off the ice · with its 80% band: 5.3 pts, 80% band 2.4 to 8.2 pts

Setup (chances his passes produced)2.31 xG11 primary assists; 0.21 expected goals per pass on average, 0.073 per 60. A pass to a tap-in counts more than a pass to a point shot.

Drive, offence+0.11expected goals created per 60 with him on, minus the club without him

Drive, defence+0.41expected goals suppressed per 60 with him on, against the club without him; positive means fewer chances allowed

Isolated impact (RAPM), offence / defence+0.01 / +0.18expected goals per 60 at 5v5 with every teammate, opponent, score state, venue and zone start held as columns of one ridge regression; ± 0.09 / 0.10 SE over 1438 minutes

Offensive-zone starts37%of his faceoffs in either end zone; heavy offensive use lifts the numbers above

Chance share, score-and-venue adjusted (5v5)55%raw 54%; each shot weighted by the league's share in that score state and venue, so trailing at home is not mistaken for tilting the ice

Finish, shrunk (goals above expected per 100 shots)-0.6raw -1.6 on 124 shots; the data carries 24% of the weight, the league the rest (about 580 shots to weight the player one half)

Company (linemates / opponents)strong / averageteammates +2.8, opponents +0.4 points of relative chance share, weighted by seconds shared

Start +/- (goals begun on his shift)723 of them were scored after he had changed off

On the ice for81 for, 86 againstthe plus/minus view, for comparison

Giveaways that led to a goal1his own turnovers inside the sequence, over 31.8 hours on the ice

Line or pairPair 1his rank by 5-on-5 ice time within the club, most common over 41 games

PartnerMiro Heiskanenshared 71% of his 5-on-5 time

Matchup65% vs first lines65% of his time against the other club's first line (hard matchups)

Shutdown (drive, defence, deployment removed)+0.46offence the same way +0.14; zone starts, opponent quality and first-line share removed by a league-wide fit

Two-way (offence + defence, deployment removed)+0.60chances created minus chances allowed per 60, against his club without him; a fast-paced player can allow more and still win here

Penalty kill76%76% of his club's penalty kill (first unit) · 320 shorthanded minutes

Matchup rating (Elo)1556above the league middle · results by who he faced over 24 hours of 5-on-5; 49% chance share against the strongest opponents he saw most (Nathan MacKinnon, Martin Necas, Quinn Hughes, Mark Scheifele, Josh Morrissey)

Finish rating (Elo)1508above the league middle · 6 goals on 119 shots worth 5 expected; rated against the goalies and the chances actually faced, so the same goal counts more against a strong goalie from a poor spot

In the play-by-play22.4 per 60how often the league's feed names him on the puck (the moments a caller says a name): 20th percentile of defencemen · drives play more than the feed shows; the feed never records carries or passes that do not end in a goal

Power-play rating (Elo)1371below the league middle · 5.48 expected goals per 60 on the power play over 63 minutes, rated against the penalty-killers faced (league rate 8.27)

Penalty-kill rating (Elo)1607above the league middle · 8.61 expected goals allowed per 60 shorthanded over 320 minutes, rated against the power-play units faced

Shot-lane rating (Elo)1471below the league middle · 119 of 186 attempts got through (64%), rated against the defenders on the ice

Lane defence rating (Elo, unit)1011bottom tenth of the league · 334 of 1565 attempts faced were blocked while he was on (21%); shared with the four others on the ice

Turnover balance-2.42 per 6028 takeaways, 105 giveaways (84 in his own end) over 31.8 hours; recorded by the league's scorers, so counts differ by rink

Blocked shots and hits5.4 · 0.9 per 60172 blocks, 29 hits given, 154 taken, 10 penalties taken

Real points293 empty-net points left out · 6 goals, 11 primary and 15 secondary assists · 2 on the power play

How these measures are defined, and where they stop.

Advanced scoring · 2025-26

Goals, assists and plus/minus, weighted by what they changed

Every goal counts the win probability it added, scaled so the average goal is 1.0: a late tying goal counts several, a goal at 6-1 or into an empty net late counts little. Plus/minus also credits the players on the ice when the goal's sequence began.

Advanced goals (aG)5.7from 6 goals · 0 clutch (worth twice an average goal or more) · +5.6 above the chances they came from

Advanced primary assists (aA1)12.0from 11 primary assists

Advanced secondary assists (aA2)13.3from 15 secondary assists; kept apart, not guessed at

Advanced points31.1against 32 scoresheet points

Advanced plus/minus (a+/-)-17.2on the ice for 91 goals for and 93 against, each weighted by what it changed · 3 of the goals for began on his shift after he had changed off · -0.54 per 60

Shot map · 2025-26

Where he shoots from, and how it goes

Every unblocked shot placed by distance, angle and shot type. His rate from each spot is set against the league's rate for the same shot from the same spot, so the edge is against everyone else taking that shot, not against an average.

His office (most-used spot)—fewer than 15 shots from any one spot

Crease (under 15 ft and inside 45°)4% of shots0 goals on 5 shots (0.0%, expected 12.9%)

Slot (under 30 ft and inside 40°)11% of shots2 goals on 13 shots (15.4%, expected 9.1%)

Circles (under 40 ft, wider)27% of shots1 goals on 32 shots (3.1%, expected 5.6%)

Point (40 ft and beyond inside 30°)42% of shots2 goals on 50 shots (4.0%, expected 2.3%)

Wall (40 ft and beyond, wide)16% of shots1 goals on 19 shots (5.3%, expected 1.3%)

Snap shots2.0%1 of 51; expected 4.5%

Wrist shots8.9%4 of 45; expected 3.2%

Slap shots10.0%1 of 10; expected 2.1%

From the video · model judgement

What the condensed games showed

Read from the league's free condensed games (1 game so far): entries, exits, battles and turnovers the model could see and attribute to his jersey number. A condensed game is a sample of the game, so these are observations, not season counts.

goals4over 1 game read

entries carried in1over 1 game read

Career arc · era-adjusted points per 82 games

Esa Lindell, season by season

Each dot is one season. The amber bar is what his earlier seasons and his age predicted for that season (80% band), so a dot far above its bar is a season the numbers did not see coming. The shaded band is where most players at his position sit at each age.

Seasons on file112015-16 to 2025-26

Best season30.62018-19, age 24, 82 games

Latest season29.5expected 12.1 to 33.2

Measured labels1exceeded ceiling

his seasonexpected range from his earlier seasonsposition, 10th to 90th percentile by ageposition median

Position band: quantile regression (10th/50th/90th) of qualifying seasons on an age spline, weighted for players who drop out.

What the numbers found

Exceeded ceiling chance at the draft of going this far past the projection: under 5%
Projection at the draft: 0 NHL hours through age 25 expected (80% band 0-18); he logged 117, above the 90th percentile.

Projection at the draft

At the draft the model expected 0 NHL hours through his age-25 season (80% band 0 to 18). He logged 117 hours, above the 90th percentile.

Every season

Season	Age	GP	Level	Expected (80%)
2015-16	21	4	0.0	−7.0 to 59.0
2016-17	22	73	21.2	6.9 to 39.6
2017-18	23	80	26.9	11.7 to 33.9
2018-19	24	82	30.6	15.3 to 36.2
2019-20	25	69	26.3	18.4 to 40.0
2020-21	26	56	23.0	16.3 to 39.2
2021-22	27	76	24.7	13.5 to 35.4
2022-23	28	82	21.7	14.0 to 35.1
2023-24	29	82	24.0	10.6 to 31.6
2024-25	30	80	25.2	12.0 to 33.1
2025-26	31	82	29.5	12.1 to 33.2

Source: CapOrCup careers desk (method and league curves) · as of 2026-09-29

Comparables at the same age

Who looked like this at 28 to 31

Careers are compared as league-adjusted points per game by age, over the same ages. The comparables below are the closest lines, and what matters is the spread of what they did next, not any single name.

Comparables found8

Went on to two or more NHL seasons7 of 8

Their later peak (adjusted pts/game)0.28median across the comparables; this player's own line is below

This player so far: age 16 Fin-U18 0.86 → age 17 Fin-Jr. 1.06 → age 18 Liiga 0.00 → age 19 Liiga 0.11 → age 20 Liiga 0.61 → age 21 AHL 0.57 → age 22 NHL 0.25 → age 23 NHL 0.34 → age 24 NHL 0.39 → age 25 NHL 0.33 → age 26 NHL 0.29 → age 27 NHL 0.33 → age 28 NHL 0.29 → age 29 NHL 0.32 → age 30 NHL 0.33 → age 31 NHL 0.39

All 3 columns shown

Player	Distance (lower is closer)	What he did afterwards
Ian ColeD · matched at ages 28, 29, 30, 31	0.06	age 32 NHL 0.15 → age 33 NHL 0.25 → age 34 NHL 0.22 → age 35 NHL 0.14 → age 36 NHL 0.21
Brian DumoulinD · matched at ages 28, 29, 30, 31	0.06	age 32 NHL 0.20 → age 33 NHL 0.26 → age 34 NHL 0.21
Brenden DillonD · matched at ages 28, 29, 30, 31	0.08	age 32 NHL 0.28 → age 33 NHL 0.26 → age 34 NHL 0.20 → age 35 NHL 0.18
Tyler MyersD · matched at ages 28, 29, 30, 31	0.08	age 32 NHL 0.22 → age 33 NHL 0.22 → age 34 NHL 0.38 → age 35 NHL 0.34 → age 36 NHL 0.14
Josh MansonD · matched at ages 28, 29, 30, 31	0.09	age 32 NHL 0.33 → age 33 NHL 0.31 → age 34 NHL 0.39
Justin HollD · matched at ages 28, 29, 30, 31	0.09	age 32 NHL 0.13 → age 33 NHL 0.11 → age 34 AHL 0.15
Vladimir DraveckyD · matched at ages 28, 30, 31	0.10	age 32 Czechia 0.17 → age 33 Czechia 0.12 → age 34 Czechia 0.16 → age 35 Czechia 0.06 → age 36 Czechia 0.12
Ben ChiarotD · matched at ages 28, 29, 30, 31	0.10	age 32 NHL 0.26 → age 33 NHL 0.16 → age 34 NHL 0.18

Reading it

If most comparables became NHL regulars and their later peak sits well above this player's current line, the numbers say there is room to grow. If most did not, the numbers say the odds are against it. Either way it is what the data shows, not a name chosen to flatter.

Atlantic

Metropolitan

Central

Pacific

Esa Lindell

How the points were built

5 LD regulars in DAL

ANA

COL

PIT

Questions a GM still has to answer

DAL do not play today

Esa Lindell is talked about more than most (74th percentile); attention is up on the usual

$5.25M cap hit