Returning regular · 2025-26

Jeff Malott

Anaheim Ducks · LW · L shot · age 30 at the dated snapshot.

Team: ANA
Lane: LW
Age: 30

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.

Games58

Goals3

Assists6

Points9

Even strength9all even-strength points

Power play0

Short handed0

Empty net0

5v5 points / 601.069

Average TOI8:49

PP TOI0:00

PK TOI0:03

Organizational context

4 LW regulars in ANA

The all-team median is 4. ANA’s farm system ranks #13 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 shots97

Expected goals7.27.4% per shot

Goals3

Finishing−4.2goals 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 quality50%3.12 expected goals for and 3.17 against per 60 minutes

Drive (vs own club without him)-1 ptshis share minus the club's share when he is off the ice

Setup (chances his passes produced)0.73 xG5 primary assists; 0.145 expected goals per pass on average, 0.088 per 60. A pass to a tap-in counts more than a pass to a point shot.

Drive, offence+0.08expected goals created per 60 with him on, minus the club without him

Drive, defence-0.24expected goals suppressed per 60 with him on, against the club without him; positive means fewer chances allowed

Offensive-zone starts47%of his faceoffs in either end zone; heavy offensive use lifts the numbers above

Company (linemates / opponents)average / averageteammates -1.6, opponents -0.3 points of relative chance share, weighted by seconds shared

Start +/- (goals begun on his shift)142 of them were scored after he had changed off

On the ice for35 for, 54 againstthe plus/minus view, for comparison

Giveaways that led to a goal0his own turnovers inside the sequence, over 8.3 hours on the ice

Line or pairLine 4his rank by 5-on-5 ice time within the club, most common over 42 games

LinematesSamuel Helenius, Taylor Wardshared 47% and 33% of his 5-on-5 time

Matchup42% vs first lines42% against the other club's first line (sheltered)

Shutdown (drive, defence, deployment removed)-0.36offence the same way -0.01; zone starts and opponent quality removed by a league-wide fit

Real points90 empty-net points left out · 3 goals, 5 primary and 1 secondary assists · 0 on the power play

How these measures are defined, and where they stop.

Comparables at the same age

Who looked like this at 26 to 29

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 seasons6 of 8

Their later peak (adjusted pts/game)0.29median across the comparables; this player's own line is below

This player so far: age 17 GOJHL 0.71 → age 18 AJHL 0.38 → age 19 AJHL 1.30 → age 20 NCAA 0.30 → age 21 NCAA 0.61 → age 22 NCAA 0.52 → age 23 NCAA 0.45 → age 24 AHL 0.59 → age 25 AHL 0.66 → age 26 AHL 0.62 → age 27 AHL 0.74 → age 28 NHL 0.08 → age 29 NHL 0.15

All 3 columns shown

Player	Distance (lower is closer)	What he did afterwards
Justin DowlingC · matched at ages 26, 27, 28, 29	0.04	age 30 NHL 0.18 → age 31 NHL 0.18 → age 32 AHL 0.37 → age 33 AHL 0.32 → age 34 NHL 0.14
Cameron LundC · matched at ages 26, 27, 28	0.08	age 30 ACH 0.32 → age 31 ACH 0.14
Zachary Aston-ReeseL · matched at ages 26, 27, 28, 29	0.09	age 30 NHL 0.21 → age 31 NHL 0.18
Michael McCarronC · matched at ages 27, 28, 29	0.10	age 30 NHL 0.19 → age 31 NHL 0.20
Radek FaksaC · matched at ages 26, 27, 28, 29	0.10	age 30 NHL 0.26 → age 31 NHL 0.21 → age 32 NHL 0.29
Anton BlidhL · matched at ages 26, 27, 28, 29	0.10	age 30 AHL 0.23 → age 31 AHL 0.11
Jonny BrodzinskiC · matched at ages 26, 27, 28, 29	0.11	age 30 NHL 0.33 → age 31 NHL 0.37 → age 32 NHL 0.29
Kurtis MacDermidL · matched at ages 26, 27, 28, 29	0.11	age 30 NHL 0.07 → age 31 NHL 0.00 → age 32 NHL 0.05

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

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Pacific