Returning regular · 2025-26

Oliver Bjorkstrand

New York Rangers · RW · R shot · age 31 at the dated snapshot.

Team: NYR
Lane: RW
Age: 31

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.

Games80

Goals12

Assists20

Points32

Even strength18all even-strength points

Power play14

Short handed0

Empty net0

5v5 points / 601.318

Average TOI13:38

PP TOI3:08

PK TOI0:00

Organizational context

6 RW regulars in NYR

The all-team median is 3.5. NYR’s farm system ranks #15 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 0.757). Finishing is goals minus expected goals; it is noisy in one season.

Unblocked shots203

Expected goals18.08.9% per shot

Goals12

Finishing−6.0goals 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 quality64%4.43 expected goals for and 2.54 against per 60 minutes

Drive (vs own club without him)+13 ptshis share minus the club's share when he is off the ice

Setup (chances his passes produced)2.12 xG15 primary assists; 0.142 expected goals per pass on average, 0.121 per 60. A pass to a tap-in counts more than a pass to a point shot.

Drive, offence+1.17expected goals created per 60 with him on, minus the club without him

Drive, defence+0.65expected goals suppressed per 60 with him on, against the club without him; positive means fewer chances allowed

Offensive-zone starts41%of his faceoffs in either end zone; heavy offensive use lifts the numbers above

Company (linemates / opponents)average / averageteammates +0.9, opponents -0.5 points of relative chance share, weighted by seconds shared

Start +/- (goals begun on his shift)526 of them were scored after he had changed off

On the ice for105 for, 80 againstthe plus/minus view, for comparison

Giveaways that led to a goal2his own turnovers inside the sequence, over 17.5 hours on the ice

Line or pairLine 3his rank by 5-on-5 ice time within the club, most common over 32 games

LinematesNick Paul, Dominic Jamesshared 31% and 27% of his 5-on-5 time

Matchup48% vs first lines48% against the other club's first line (sheltered)

Shutdown (drive, defence, deployment removed)+0.40offence the same way +0.99; zone starts and opponent quality removed by a league-wide fit

Real points320 empty-net points left out · 12 goals, 15 primary and 5 secondary assists · 14 on the power play

How these measures are defined, and where they stop.

Comparables at the same age

Who looked like this at 27 to 30

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 seasons8 of 8

Their later peak (adjusted pts/game)0.72median across the comparables; this player's own line is below

This player so far: age 14 Den-U17 1.60 → age 15 Den-U17 2.84 → age 16 Denmark 0.72 → age 17 WHL 0.97 → age 18 WHL 1.58 → age 19 WHL 2.00 → age 20 NHL 0.67 → age 21 NHL 0.50 → age 22 NHL 0.49 → age 23 NHL 0.47 → age 24 NHL 0.73 → age 25 NHL 0.79 → age 26 NHL 0.71 → age 27 NHL 0.56 → age 28 NHL 0.72 → age 29 NHL 0.61 → age 30 NHL 0.40

All 3 columns shown

Player	Distance (lower is closer)	What he did afterwards
Jason ZuckerL · matched at ages 27, 28, 29, 30	0.08	age 31 NHL 0.61 → age 32 NHL 0.49 → age 33 NHL 0.73 → age 34 NHL 0.73
Tom WilsonR · matched at ages 27, 28, 29, 30	0.09	age 31 NHL 0.80 → age 32 NHL 0.86
Nino NiederreiterR · matched at ages 27, 28, 29, 30	0.10	age 31 NHL 0.44 → age 32 NHL 0.45 → age 33 NHL 0.31
Jordan StaalC · matched at ages 27, 28, 29, 30	0.10	age 31 NHL 0.40 → age 32 NHL 0.72 → age 33 NHL 0.46 → age 34 NHL 0.42 → age 35 NHL 0.38
Blake ColemanL · matched at ages 27, 28, 29, 30	0.10	age 31 NHL 0.46 → age 32 NHL 0.69 → age 33 NHL 0.48 → age 34 NHL 0.51
Kyle PalmieriC · matched at ages 27, 28, 29, 30	0.10	age 31 NHL 0.48 → age 32 NHL 0.60 → age 33 NHL 0.66 → age 34 NHL 0.58 → age 35 NHL 0.72
Mikael BacklundC · matched at ages 27, 28, 29, 30	0.11	age 31 NHL 0.64 → age 32 NHL 0.59 → age 33 NHL 0.48 → age 34 NHL 0.68 → age 35 NHL 0.48
Rickard RakellR · matched at ages 27, 28, 29, 30	0.12	age 31 NHL 0.86 → age 32 NHL 0.80

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

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Pacific