xJawn NHL expected goals

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New Jersey Devils

Metropolitan · 13-5-0, 26 pts

18 GP · 2nd Metropolitan
2026-27 · regular season
On the ice
Adjusts with rink filters
shots for◀ 5v5 offense
shots against5v5 defense ▶
How to read this map

One rink, both ends: what NJD generates on the left, what it concedes on the right (on a phone, one end at a time, net at the top: the switch above the map picks it). Every attempt is a Gaussian bump of height = its model xG, summed per game. The controls switch the surface (xG heatmap ↔ vs league, the league baseline at the same strength) and the markers: × goal · • on net · ◦ missed · small • blocked.

The page opens at 5v5; empty-net attempts are excluded throughout, and the strength buckets segregate them anyway — which is why the empty-net control greys out unless the view can actually contain one. Everything inside the outlined box moves with the filters; everything below it does not.

Observed production

5v5 · season to date
for against
axis spans ±63% of league average · centre = average · right = more
Goalsteam
43 88th pctl35 53rd pctl
Shotsteam
480 97th pctl363 48th pctl
Attemptsteam
973 97th pctl735 34th pctl
xGteam
43.1 97th pctl32.0 25th pctl
xGF%share of team xG
57.4%94th pctl
0% 50% = even split · gray = league middle 50% / 90% 100%

Percentiles and the gray spread rank against all 32 teams recomputed under the current filter — every bar and band here moves together, so a slice never ranks against a different slice's league.

Rolling xGF%

5v5 · last 10 games
Per-game chance share, smoothed. drag the slider to set the window
Who

Skaters on ice

5v5 · season to date
Team expected goals while each skater is on the ice, per 60 minutes · 5v5. up and right is better
strength
xGF/60 xGA/60
centre = league skater average · gray = league middle 50% / 90%
SkaterPos TOIxGF/60 xGA/60xGF% for / against
Jesper Bratt F 312 5.21 1.74 75.0%
Luke Evangelista F 256 4.49 1.67 72.9%
Jack Hughes F 370 5.07 1.91 72.7%
Nico Hischier F 325 4.62 2.17 68.1%
Arseny Gritsyuk F 280 3.67 2.12 63.4%
Luke Hughes D 439 3.76 2.40 61.1%
Timo Meier F 297 3.44 2.22 60.7%
Anthony Mantha F 228 3.14 2.11 59.9%
Jesper Boqvist F 193 2.74 1.89 59.3%
Dougie Hamilton D 369 3.72 2.59 58.9%
Declan Chisholm D 228 2.82 2.09 57.5%
Johnathan Kovacevic D 183 2.48 1.91 56.5%
Amadeus Lombardi F 183 2.92 2.44 54.5%
Jonas Siegenthaler D 352 2.87 2.56 52.9%
Connor Brown F 146 2.62 2.35 52.8%
Brenden Dillon D 130 2.50 2.36 51.4%
Brett Pesce D 379 2.60 2.53 50.6%
Dawson Mercer F 151 2.58 2.81 47.9%
Evan Rodrigues F 274 2.28 2.63 46.5%
Cody Glass F 220 2.32 2.75 45.7%
xGF/60 xGA/60
centre = league skater average · gray = league middle 50% / 90%
SkaterPos TOIxGF/60 xGA/60xGF% for / against
Jesper Bratt F 235 3.64 2.12 63.2%
Jack Hughes F 286 3.61 2.11 63.1%
Luke Evangelista F 203 3.06 1.84 62.5%
Arseny Gritsyuk F 248 3.34 2.10 61.4%
Nico Hischier F 227 3.28 2.08 61.1%
Johnathan Kovacevic D 177 2.57 1.80 58.8%
Timo Meier F 249 2.94 2.10 58.3%
Brett Pesce D 339 2.77 1.99 58.2%
Brenden Dillon D 119 2.52 1.83 57.9%
Jesper Boqvist F 185 2.50 1.82 57.9%
Dougie Hamilton D 301 3.35 2.45 57.8%
Declan Chisholm D 221 2.69 2.00 57.3%
Jonas Siegenthaler D 315 3.11 2.34 57.1%
Luke Hughes D 337 2.71 2.22 54.9%
Anthony Mantha F 202 2.59 2.19 54.3%
Dawson Mercer F 125 2.59 2.22 53.8%
Amadeus Lombardi F 176 2.69 2.45 52.4%
Cody Glass F 186 2.32 2.17 51.6%
Evan Rodrigues F 221 1.96 2.18 47.4%
Connor Brown F 117 1.76 2.22 44.3%
xGF/60 xGA/60
centre = league skater average · gray = league middle 50% / 90%
SkaterPos TOIxGF/60 xGA/60xGF% for / against
Nico Hischier F 60 11.45 0.15 98.7%
Luke Hughes D 61 10.33 0.15 98.5%
Jesper Bratt F 60 10.68 0.20 98.2%
Luke Evangelista F 46 10.61 0.23 97.9%
Jack Hughes F 65 10.75 0.28 97.4%
Connor Brown F 14 12.17 0.35 97.2%
Dougie Hamilton D 31 9.66 0.87 91.8%
Evan Rodrigues F 27 6.60 0.74 89.9%
Arseny Gritsyuk F 24 8.32 0.97 89.6%
Timo Meier F 30 6.78 0.88 88.5%
Anthony Mantha F 26 7.56 1.03 88.0%
xGF/60 xGA/60
centre = league skater average · gray = league middle 50% / 90%
SkaterPos TOIxGF/60 xGA/60xGF% for / against
Luke Hughes D 22 0.73 8.50 7.9%
Cody Glass F 23 0.50 6.98 6.7%
Nico Hischier F 23 0.48 7.27 6.2%
Connor Brown F 11 0.34 5.26 6.1%
Dawson Mercer F 18 0.44 6.97 5.9%
Brenden Dillon D 9 0.49 8.52 5.4%
Brett Pesce D 29 0.47 8.46 5.2%
Evan Rodrigues F 23 0.49 9.35 5.0%
Jonas Siegenthaler D 28 0.20 4.68 4.2%
Dougie Hamilton D 26 0.22 5.76 3.6%
How to read this section

Each skater is placed by the team's expected goals for (across) and against (up, reversed so fewer is higher) per 60 minutes while they are on the ice. Above the dashed line the team out-chances its opponents with that skater on; below it, it is out-chanced. The dotted lines are the league skater average, and the open ring is the NJD average. Bigger markers mean more ice time; circles are forwards, diamonds defensemen.

5v5 is even strength with both goalies in. All is every strength, with shots at an empty net left out, as on the rink above. Power play is more skaters than the opponent with NJD's goalie in (an extra attacker for a pulled goalie is not one); penalty kill is fewer, with the opponent's goalie in. The strength switch is the page's: it moves the rink above too, and the link carries it. On-ice numbers describe what happened with a skater on the ice, teammates and opponents included; the Players page's RAPM separates the skater from both.

Skaters under 66 minutes at 5v5 for NJD are left off the chart and folded under the table; the floor grows with games played. On the power play and the kill a skater also needs half a minute a game at that strength, so the dots there are the units, not whoever got a shift. A traded skater counts only their time with this club. Once the playoffs start, their games count here too.

The model

Model estimates

🔒 5v5 · as of Jun 14, 2026
Season-long ratings — the filters above don't apply here. goals vs league average · bar grows from average

Last season's ratings on this season's shots. The per-player ratings behind these rows were fit as of 2026-06-14, before 2026-27 opened, and stay fixed until the season has enough games to refit. They are applied to the shots 2026-27 has actually seen, so the rows update daily; a player the fit never saw counts as league average.

Shootingour skaters · on our shots, vs this season's average
-0.825th pctl
973 attempts · 95% by rated shooters
Savingour goalies · on shots faced, vs this season's average
Connor Hellebuyck +0.42 G · 195 shotsNico Daws -0.24 G · 135 shotsJake Allen +0.02 G · 405 shots
+0.256th pctl
Jake Allen 405 · Connor Hellebuyck 195 · Nico Daws 135 shots faced
Shooting againsttheir skaters · on shots faced
-0.513th pctl
sign-flipped — positive means they shot worse than average
Saving againsttheir goalies · on our shots
-0.513th pctl
negative means their goalies stopped more than average
−4league average+4

These four are shown within-season centered — each against this season's own league average, not the fit's career-pooled one — because shooting talent leaguewide is running well above its historical zero point this season; without that adjustment nearly every bar would read "above average." The against columns still barely vary between teams, since every team faces roughly average opposition, so for those two the rank still matters more than the level. They are shown because they genuinely move adjusted xGF% below (computed from the uncentered ratings — see that section's own note), and folding them into the two own-team rows would have hidden half of that.

Adjusted xGF%skill-weighted chance share
shooting +0.72 ppsaving against -1.30 ppshooting against -1.53 ppsaving +1.17 pp
56.5%91st pctl · -0.94 pp
0% 50% = even split · gray = league middle 50% / 90% 100%
How it's built, and what it isn't
unadjusted 57.4% +shooting +0.72+saving against -1.30+shooting against -1.53+saving +1.17 = adjusted 56.5%

How it's builtEvery 5v5 shot is re-scored with σ(logit(xG) + shooter − goalie) and both ends re-summed. Both skill terms land on every shot — one team's for side, the other's against side — so the league share still averages 50%. The two moves are taken in that order and sum exactly to the total; shares don't decompose additively, so a side-by-side split would not close.

What it isn'tA descriptive re-score of shots already taken, not a forecast. Against future goal share the combined adjustment is indistinguishable from plain xGF% (+0.019 r, p = 0.192); only the shooting half shows a small honest lift (+0.026, p = 0.020), and the saving half contributes nothing forward-looking. The premise underneath is itself unestablished — xGF% over GF% is +0.040, p = 0.246. Read it as what this roster's skill was worth on these shots — nothing more.

The four segments are the four rows above, in order. They are four and not two because η puts both rating terms on every shot: the shots we took carry our shooters and the opposing goalie, and the shots we faced carry their shooters and ours. Over a full season the two “against” terms would sit near league average and contribute nothing — but the ratings are not centred at zero this season, so they do move the number, and hiding them inside a single “shots faced” figure would have left half the adjustment unexplained.

Context

Season context

season to date
How the season was played, not how well. Not a modeled component: each is its own metric (a rate, a TOI share, or opponents' net xG-RAPM), shown with a league percentile only where one exists, never added together. Not a grade.
Ice timeshare by strength
5v5 84%PPPK
+1.7PP − PK min/60
Score stateTOI by game state
trail 25%tied 36%lead 39%
leads a lot
Goalie workloadstarter's share of shots
55%of 5v5 shots against
Schedule strengthopponents' net xG-RAPM
not available in the pipeline
—
0league average100 pctl
Full table · all numbers
FamilyStatValue (current slice)
Observed ◆ filtered Goals for / against 43 / 35
Observed ◆ filtered xG for / against 43.1 / 32.0
Observed ◆ filtered Shots for / against 480 / 363
Observed ◆ filtered Attempts for / against 973 / 735
Modeled 🔒 5v5 Shooting — our skaters · on our shots, vs this season's average -0.8 G 25th pctl
Modeled 🔒 5v5 Saving — our goalies · on shots faced, vs this season's average +0.2 G 56th pctl
Modeled 🔒 5v5 Shooting against — their skaters · on shots faced -0.5 G 13th pctl
Modeled 🔒 5v5 Saving against — their goalies · on our shots -0.5 G 13th pctl
Modeled 🔒 5v5Unadjusted xGF%57.4%
Modeled 🔒 5v5↳ shooting shift+0.72 pp
Modeled 🔒 5v5↳ saving against shift-1.30 pp
Modeled 🔒 5v5↳ shooting against shift-1.53 pp
Modeled 🔒 5v5↳ saving shift+1.17 pp
Modeled 🔒 5v5Adjusted xGF% 56.5% 91st pctl
ContextIce time — share by strength+1.7
ContextScore state — TOI by game stateleads a lot
ContextGoalie workload — starter's share of shots55%
ContextSchedule strength — opponents' net xG-RAPM—

Observed values reflect the active rink filters; modeled values are fixed at their 5v5 fit.

Modeled ratings come from joint__baseline_xg__f3e3111e (as of 2026-06-14) — a separate surface from the box-score xG model badged in the footer.