Points by season
Career NHL points, ending with the 84-game projection (violet).
Pool value
Projected full-season fantasy worth.
why 25?
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 goals2 × 3+6
- proj assists10 × 1+10
- PP points0 × 0.5+0
- game-winning goals0 × 0.5+0
- OT goals0 × 0.25+0
- shots84 × 0.1+8.4
- PIM47 × 0.05+2.4
- ice time (min)1520 × 0.01+15.2
- total42 pool points · an elite defenseman season scores 16642 = 25/100
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 defensemen in the NHL — an elite season scores about 166 points, and that is what 100 means. So 42 points is 25 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 (18 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
- Off the net: 0.7 SOG/game lately vs 1.3 before — chances have dried up.
- Every night: in the lineup for all of the team's last 10 games.
- Availability: every game this season — 15 of 15 for TBL.
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 underperforming O/U ▼ −1.3
- TRADE VALUE: BELOW PACE — mildly. Cheap production relative to the underlying play.
- 0.0% shooting on 18 shots against HIS OWN career baseline of 6.7% (369 shots before this season) — that's 1.2 goals below what his shot volume normally buys for him (1.2 expected goals). under pace. His shrunk talent rate is 5.2%, worth PD −1.3 goals per 84 over/under his own standard.
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Coyotes | 43 | 4 | 11 | 15 | -10 | 16 | 1 | 2 | 0 | 18:42 | 1 | 0 | 40 | 10.0% | 0.0% |
| 2022-23 | Coyotes | 82 | 7 | 24 | 31 | -12 | 35 | 3 | 11 | 0 | 21:03 | 1 | 0 | 93 | 7.5% | 0.0% |
| 2023-24 | Coyotes | 80 | 5 | 21 | 26 | -5 | 35 | 0 | 3 | 0 | 20:34 | 0 | 0 | 77 | 6.5% | 0.0% |
| 2024-25 | Lightning | 54 | 2 | 12 | 14 | 20 | 22 | 0 | 1 | 1 | 18:51 | 0 | 0 | 48 | 4.2% | 0.0% |
| 2025-26 | Lightning | 79 | 7 | 22 | 29 | 41 | 69 | 0 | 1 | 0 | 21:34 | 0 | 0 | 111 | 6.3% | 0.0% |
| 2026-27 | Lightning | 19 | 0 | 1 | 1 | 3 | 10 | 0 | 0 | 0 | 18:24 | 0 | 0 | 19 | 0.0% | 0.0% |
| 84-G proj | Lightning | 84 | 2 | 10 | 13 | — | 48 | — | 1 | — | 18:29 | — | — | 92 | — | — |
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 26 that is 0%. Dashes mark stats the model doesn't project.
Comparable player-seasons: Erik Gudbranson (2025-25) · Jeremy Lauzon (2025-25) · Haydn Fleury (2025-25) · Brett Pesce (2025-25) · Jaycob Megna (2023-23).
Goals — with the line
| Time | ST | Type | Goal | His line | Opp ice |
|---|---|---|---|---|---|
| Nov 3 · vs DET | |||||
| P2 08:41 | EV | Assist | #? (Goncalves, Moser) → 3-0 | Hagel · Goncalves Crozier · Moser | Copp · Raymond · Mazur Faulk · Wallinder Tarasov (G) |
Line mates
Teammates sharing the most ice time with J.J. over the last 10 games — reconstructed shift-by-shift from the NHL's official timing feed (goalies excluded).
| Player | Shared min | GP | |
|---|---|---|---|
| Victor Hedman TBL | 64 | 10 | |
| Brandon Hagel TBL | 59 | 10 | |
| Anthony Cirelli TBL | 53 | 9 | |
| Ryan McDonagh TBL | 51 | 10 | |
| Nikita Kucherov TBL | 50 | 10 |
Data via the public NHL API · 2026 Pro Hockey Stats