Points by season
Career NHL points, ending with the 84-game projection (violet).
Pool value
Projected full-season fantasy worth.
why 50?
Each row is one fantasy category turned into points over a full 84-game season. Add the rows up and that is his total fantasy worth.
- proj goals17 × 3+51
- proj assists41 × 1+41
- PP points15 × 0.5+7.5
- game-winning goals0 × 0.5+0
- OT goals0 × 0.25+0
- shots79 × 0.1+7.9
- PIM10 × 0.05+0.5
- ice time (min)1204 × 0.01+12
- total120 pool points · an elite forward season scores 242120 = 50/100
Weights follow what the average fantasy league actually counts: goals at 3× assists (the universal core), power-play points and game-winners at half weight (common extra categories), OT goals, shots and PIM small (many leagues skip them), and ice time as a quiet availability bonus. The scale: add up a whole season of those categories and compare against the best forwards in the NHL — an elite season scores about 242 points, and that is what 100 means. So 120 points is 50 out of a perfect fantasy season at his position. Defensemen and forwards are graded on separate scales because the D slot can only be filled by a defenseman. Goals and assists come from the backtested season model; the rest ride your own season-to-date pace over 84 games (17 games so far — small sample, secondary lines will move as roles settle). Hits/blocks are excluded: the free NHL feeds don't publish full-season totals, and we don't invent them.
The Situation
- Every night: in the lineup for all of the team's last 10 games.
- Availability: every game this season — 12 of 12 for SEA.
Every line is measured from our own boxscore ledger; absence reasons from the NHL Status Report and our transaction wire only — no insider guessing.
Finishing check on pace O/U • +1.0
- TRADE VALUE: AT PACE — trade value is what the numbers say it is.
- 18.8% shooting on 16 shots against HIS OWN career baseline of 12.8% (663 shots before this season) — that's 0.9 goals above what his shot volume normally buys for him (2.1 expected goals). on pace. His shrunk talent rate is 14.1%, worth PD +1.0 goals per 84 over/under his own standard.
- His goals track his shot volume almost exactly — what you see is what you have.
Model: goals vs shot volume vs live league position baselines; talent SH% is an empirical-Bayes shrinkage of the season…
His shooting talent is estimated by shrinking his season shooting percentage toward his league position mean in proportion to sample size (kappa pseudo-shots prior), then projecting the gap over 84 games at his current shot volume. Small samples stay near zero — the number only moves when the evidence does.
The method follows published hockey-analytics research: a shooter is judged against his own career shooting percentage, because a player's own career rate predicts his next goals better than any league average (“Expected by Whom? A Skill-Adjusted Expected Goals Model for NHL Shooters and Goaltenders,” arXiv:2511.07703). Thin careers (rookies) shrink toward the league mean for the position, and the season number is shrunk toward the player's own anchor with empirical-Bayes weights — Nandakumar & Jensen (2019), Annual Review of Statistics and Its Application, doi:10.1146/annurev-statistics-030718-105202. This section is about the gap between luck and his pace, not talent.
Season stats
NHL regular-season totals, season by season. The 84-G proj line extends the current season with our public model — methodology in the caption below the table.
| Season | Team | GP | G | A | P | +/- | PIM | PPG | PPP | SHG | TOI/GP | GWG | OTG | S | S% | FOW% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Rangers | 66 | 10 | 13 | 23 | -26 | 14 | 2 | 13 | 0 | 14:17 | 3 | 1 | 109 | 9.2% | 33.3% |
| 2020-21 | Rangers | 48 | 9 | 8 | 17 | 3 | 10 | 2 | 3 | 0 | 14:21 | 0 | 0 | 81 | 11.1% | 42.9% |
| 2021-22 | Rangers | 43 | 7 | 11 | 18 | 9 | 10 | 1 | 2 | 0 | 15:27 | 2 | 0 | 62 | 11.3% | 14.3% |
| 2022-23 | Rangers | 82 | 18 | 22 | 40 | 12 | 8 | 0 | 3 | 0 | 15:18 | 2 | 0 | 125 | 14.4% | 25.0% |
| 2023-24 | Rangers | 61 | 13 | 6 | 19 | 6 | 24 | 1 | 1 | 0 | 13:17 | 2 | 0 | 91 | 14.3% | 56.5% |
| 2024-25 | Rangers | 30 | 4 | 10 | 14 | 9 | 14 | 1 | 2 | 0 | 13:17 | 1 | 0 | 45 | 8.9% | 50.0% |
| 2024-25 | Kraken | 49 | 10 | 20 | 30 | -11 | 24 | 3 | 6 | 0 | 17:03 | 1 | 0 | 72 | 13.9% | 50.0% |
| 2025-26 | Kraken | 65 | 13 | 27 | 40 | 14 | 14 | 2 | 8 | 0 | 14:15 | 2 | 0 | 78 | 16.7% | 45.9% |
| 2026-27 | Kraken | 17 | 3 | 10 | 13 | 2 | 2 | 0 | 3 | 0 | 14:20 | 0 | 0 | 16 | 18.8% | 0.0% |
| 84-G proj | Kraken | 84 | 17 | 41 | 58 | — | 24 | — | 11 | — | 14:41 | — | — | 110 | — | — |
84-G proj — current pace blended with the player's own history (recent seasons weighted heaviest), mixed with a similarity projection from historical players with comparable profiles, then adjusted for the aging curve (league-average peak at 27; decline after) — at age 25 that is 1%. Dashes mark stats the model doesn't project.
Comparable player-seasons: Patrick Kane (2025-25) · J.T. Miller (2025-25) · Jakub Voracek (2021-21) · Roope Hintz (2025-25) · Jesper Bratt (2025-25).
Goals — with the line
| Time | ST | Type | Goal | His line | Opp ice |
|---|---|---|---|---|---|
| Nov 7 · vs NYR | |||||
| P3 01:50 | EV | Goal | #? (Montour, Catton) → 1-4 | Wood · Catton Montour · Evans | Tolvanen · Dorofeyev · Cuylle Robertson · Morrow Korpisalo (G) |
| Nov 4 · vs CGY | |||||
| P2 13:09 | EV | Assist | #? (Samoskevich, Kakko) → 1-1 | Kakko · Samoskevich Mahura · Ottavainen | Frost · Sharangovich · Suniev Kuznetsov · Parekh Wolf (G) |
| Oct 30 · @ CGY | |||||
| P2 18:15 | PP | Assist | #? (Kakko, Catton) → 2-4 | Kakko · Wright · Catton Montour | Backlund · Farabee Middleton · Whitecloud Wolf (G) |
| Oct 24 · vs MIN | |||||
| P1 10:13 | EV | Assist | Catton (Kakko, Montour) → 1-1 | Samoskevich · Catton · Wright · Kakko Montour | Trenin · Yurov · McCarron Brodin · Spurgeon Wallstedt (G) |
| Oct 22 · vs UTA | |||||
| P1 18:23 | PP | Assist | Beniers (Kakko, Catton) → 2-1 | Beniers · Samoskevich · Catton · Kakko Montour | Trocheck · Crouse Weegar · Sergachev Vejmelka (G) |
Line mates
Teammates sharing the most ice time with Kaapo over the last 10 games — reconstructed shift-by-shift from the NHL's official timing feed (goalies excluded).
| Player | Shared min | GP | |
|---|---|---|---|
| Berkly Catton SEA | 126 | 10 | |
| Shane Wright SEA | 81 | 7 | |
| Brandon Montour SEA | 57 | 9 | |
| Ryker Evans SEA | 51 | 10 | |
| Adam Larsson SEA | 41 | 10 |
Data via the public NHL API · 2026 Pro Hockey Stats