Returning regular · 2025-26

Charlie McAvoy

Boston Bruins · RD · R shot · age 28 at the dated snapshot.

Team: BOS
Lane: RD
Age: 28

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.

Games69

Goals11

Assists50

Points61

Even strength38all even-strength points

Power play23

Short handed0

Empty net4

5v5 points / 601.532

Average TOI24:23

PP TOI3:04

PK TOI2:48

Organizational context

4 RD regulars in BOS

The all-team median is 4. BOS’s farm system ranks #18 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 shots187

Expected goals9.24.9% per shot

Goals11

Finishing+1.8goals 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 quality48%3.67 expected goals for and 4.02 against per 60 minutes

Drive, three seasons (ranking measure)+1.0 pts5v5 chance share against his club without him, over this season and the two before (weights 1 / 0.7 / 0.4; 1174 / 870 / 1340 minutes) · 80% band -1.0 to 3.3 pts. This is the number the rankings order by: it predicts next season better than one season does.

Drive, this season only+1 ptsat 5-on-5, over 19.6 hours: his share minus the club's share when he is off the ice · with its 80% band: 0.6 pts, 80% band -2.8 to 4.0 pts

Setup (chances his passes produced)4.59 xG30 primary assists; 0.153 expected goals per pass on average, 0.164 per 60. A pass to a tap-in counts more than a pass to a point shot.

Drive, offence+0.33expected goals created per 60 with him on, minus the club without him

Drive, defence-0.30expected goals suppressed per 60 with him on, against the club without him; positive means fewer chances allowed

Isolated impact (RAPM), offence / defence+0.08 / -0.09expected 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 1174 minutes

Offensive-zone starts50%of his faceoffs in either end zone; heavy offensive use lifts the numbers above

Chance share, score-and-venue adjusted (5v5)48%raw 48%; 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)0.0raw +0.7 on 187 shots; the data carries 31% of the weight, the league the rest (about 580 shots to weight the player one half)

Company (linemates / opponents)average / averageteammates +1.2, opponents -0.2 points of relative chance share, weighted by seconds shared

Start +/- (goals begun on his shift)944 of them were scored after he had changed off

On the ice for118 for, 97 againstthe plus/minus view, for comparison

Giveaways that led to a goal2his own turnovers inside the sequence, over 28 hours on the ice

Line or pairPair 1his rank by 5-on-5 ice time within the club, most common over 40 games

PartnerJonathan Aspirotshared 42% of his 5-on-5 time

Matchup63% vs first lines63% of his time against the other club's first line (hard matchups)

Shutdown (drive, defence, deployment removed)-0.26offence the same way +0.13; zone starts, opponent quality and first-line share removed by a league-wide fit

Two-way (offence + defence, deployment removed)-0.13chances created minus chances allowed per 60, against his club without him; a fast-paced player can allow more and still win here

Penalty kill51%51% of his club's penalty kill (first unit) · 193 shorthanded minutes

Matchup rating (Elo)1517above the league middle · results by who he faced over 19.6 hours of 5-on-5; 54% chance share against the strongest opponents he saw most (J.J. Moser, Nikita Kucherov, Bowen Byram, Owen Power, Jake Guentzel)

Finish rating (Elo)1515above the league middle · 11 goals on 186 shots worth 9.6 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-play27.2 per 60how often the league's feed names him on the puck (the moments a caller says a name): 64th percentile of defencemen; the feed never records carries or passes that do not end in a goal

Power-play rating (Elo)1422above the league middle · 8.96 expected goals per 60 on the power play over 209 minutes, rated against the penalty-killers faced (league rate 8.27)

Penalty-kill rating (Elo)1543below the league middle · 9.52 expected goals allowed per 60 shorthanded over 193 minutes, rated against the power-play units faced

Shot-lane rating (Elo)1508below the league middle · 179 of 259 attempts got through (69%), rated against the defenders on the ice

Lane defence rating (Elo, unit)1121bottom tenth of the league · 401 of 1637 attempts faced were blocked while he was on (25%); shared with the four others on the ice

Turnover balance-2.07 per 6028 takeaways, 86 giveaways (63 in his own end) over 28 hours; recorded by the league's scorers, so counts differ by rink

Blocked shots and hits4.3 · 2.7 per 60121 blocks, 76 hits given, 110 taken, 31 penalties taken

Real points574 empty-net points left out · 11 goals, 30 primary and 20 secondary assists · 23 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)11.0from 11 goals · 2 clutch (worth twice an average goal or more) · +10.0 above the chances they came from

Advanced primary assists (aA1)35.9from 30 primary assists

Advanced secondary assists (aA2)22.8from 20 secondary assists; kept apart, not guessed at

Advanced points69.7against 61 scoresheet points

Advanced plus/minus (a+/-)+25.3on the ice for 128 goals for and 104 against, each weighted by what it changed · 4 of the goals for began on his shift after he had changed off · +0.90 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°)5% of shots2 goals on 10 shots (20.0%, expected 15.2%)

Slot (under 30 ft and inside 40°)9% of shots4 goals on 17 shots (23.5%, expected 12.5%)

Circles (under 40 ft, wider)27% of shots2 goals on 50 shots (4.0%, expected 6.7%)

Point (40 ft and beyond inside 30°)43% of shots3 goals on 79 shots (3.8%, expected 2.8%)

Wall (40 ft and beyond, wide)16% of shots0 goals on 30 shots (0.0%, expected 1.2%)

Wrist shots2.6%2 of 76; expected 4.5%

Slap shots4.3%2 of 46; expected 4.4%

Snap shots4.5%2 of 44; expected 5.7%

Backhand shots10.0%1 of 10; expected 7.1%

Career arc · era-adjusted points per 82 games

Charlie McAvoy, 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 file92017-18 to 2025-26

Best season66.92025-26, age 28, 69 games

Latest season66.9expected 31.9 to 54.3

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: 8%
Projection at the draft: 80 NHL hours through age 25 expected (80% band 18-137); he logged 146, above the 90th percentile.

Projection at the draft

At the draft the model expected 80 NHL hours through his age-25 season (80% band 18 to 137). He logged 146 hours, above the 90th percentile.

Every season

Season	Age	GP	Level	Expected (80%)
2017-18	20	63	40.5	9.1 to 42.5
2018-19	21	54	40.7	28.6 to 52.9
2019-20	22	67	37.6	32.0 to 54.6
2020-21	23	51	47.4	29.4 to 53.0
2021-22	24	78	53.8	33.7 to 55.5
2022-23	25	67	57.6	39.9 to 61.8
2023-24	26	74	48.1	44.1 to 65.7
2024-25	27	50	35.7	38.2 to 61.9
2025-26	28	69	66.9	31.9 to 54.3

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

Comparables at the same age

Who looked like this at 25 to 28

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)0.87median across the comparables; this player's own line is below

This player so far: age 14 AYHL 14U 0.27 → age 15 MetJHL 1.29 → age 16 USHL 0.29 → age 17 USHL 0.83 → age 18 NCAA 0.68 → age 19 NCAA 0.68 → age 20 NHL 0.51 → age 21 NHL 0.52 → age 22 NHL 0.48 → age 23 NHL 0.59 → age 24 NHL 0.72 → age 25 NHL 0.78 → age 26 NHL 0.64 → age 27 NHL 0.46 → age 28 NHL 0.88

All 3 columns shown

Player	Distance (lower is closer)	What he did afterwards
John CarlsonD · matched at ages 25, 26, 27, 28	0.07	age 29 NHL 0.88 → age 30 NHL 1.09 → age 31 NHL 0.85 → age 32 NHL 0.91 → age 33 NHL 0.72
Morgan RiellyD · matched at ages 25, 26, 27, 28	0.11	age 29 NHL 0.63 → age 30 NHL 0.81 → age 31 NHL 0.50 → age 32 NHL 0.46
Drew DoughtyD · matched at ages 25, 26, 27, 28	0.14	age 29 NHL 0.55 → age 30 NHL 0.52 → age 31 NHL 0.61 → age 32 NHL 0.80 → age 33 NHL 0.64
Shea TheodoreD · matched at ages 25, 26, 27, 28	0.14	age 29 NHL 0.85 → age 30 NHL 0.56
Roman JosiD · matched at ages 25, 26, 27, 28	0.16	age 29 NHL 0.94 → age 30 NHL 0.69 → age 31 NHL 1.20 → age 32 NHL 0.88 → age 33 NHL 1.04
Josh MorrisseyD · matched at ages 25, 26, 27, 28	0.20	age 29 NHL 0.85 → age 30 NHL 0.78 → age 31 NHL 0.71
Brent BurnsD · matched at ages 25, 26, 27, 28	0.21	age 29 NHL 0.70 → age 30 NHL 0.73 → age 31 NHL 0.92 → age 32 NHL 0.93 → age 33 NHL 0.82
Kris LetangD · matched at ages 25, 26, 27, 28	0.23	age 29 NHL 0.83 → age 30 NHL 0.65 → age 31 NHL 0.86 → age 32 NHL 0.72 → age 33 NHL 0.82

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