Columbus Blue Jackets
Metropolitan · 7-8-0, 14 pts
2026-27 · regular season
shots for◀ 5v5 offense
How to read this map
One rink, both ends: what CBJ 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 datePercentiles 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 gamesSkaters on ice
5v5 · season to date| Skater | Pos | TOI | xGF/60 | xGA/60 | xGF% | for / against |
|---|---|---|---|---|---|---|
| Kent Johnson | F | 267 | 3.22 | 2.16 | 59.9% | |
| Matthew Knies | F | 272 | 3.01 | 2.32 | 56.5% | |
| Dmitri Voronkov | F | 98 | 3.04 | 2.38 | 56.1% | |
| Adam Fantilli | F | 311 | 2.96 | 2.49 | 54.3% | |
| Charlie Coyle | F | 297 | 3.55 | 3.00 | 54.2% | |
| Zach Werenski | D | 423 | 3.16 | 3.44 | 47.9% | |
| Damon Severson | D | 289 | 2.85 | 3.20 | 47.1% | |
| Ryan Lomberg | F | 118 | 2.01 | 2.27 | 47.0% | |
| Cole Sillinger | F | 232 | 2.83 | 3.32 | 46.0% | |
| Denton Mateychuk | D | 337 | 2.39 | 2.91 | 45.0% | |
| Conor Garland | F | 202 | 2.15 | 2.62 | 45.0% | |
| Mathieu Olivier | F | 233 | 2.67 | 3.28 | 45.0% | |
| Danton Heinen | F | 102 | 1.94 | 2.39 | 44.9% | |
| Valeri Nichushkin | F | 250 | 2.29 | 2.97 | 43.5% | |
| Ivan Provorov | D | 86 | 2.71 | 3.65 | 42.6% | |
| Jake Christiansen | D | 195 | 1.83 | 2.75 | 39.9% | |
| Sean Monahan | F | 243 | 2.39 | 4.27 | 35.9% | |
| Dante Fabbro | D | 87 | 1.40 | 2.57 | 35.2% | |
| Carson Soucy | D | 103 | 1.57 | 3.12 | 33.5% | |
| Erik Gudbranson | D | 185 | 1.34 | 3.94 | 25.4% | |
| Luca Del Bel Belluz | F | 61 | 1.44 | 2.37 | 37.8% | |
| Emil Andrae | D | 53 | 1.84 | 2.17 | 46.0% | |
| Jack Williams | F | 10 | 3.44 | 3.96 | 46.5% | |
| Steven Lorentz | F | 9 | 1.83 | 1.91 | 48.9% |
| Skater | Pos | TOI | xGF/60 | xGA/60 | xGF% | for / against |
|---|---|---|---|---|---|---|
| Charlie Coyle | F | 202 | 3.16 | 2.28 | 58.0% | |
| Ivan Provorov | D | 68 | 3.14 | 2.55 | 55.1% | |
| Mathieu Olivier | F | 205 | 2.94 | 2.58 | 53.3% | |
| Dmitri Voronkov | F | 88 | 2.70 | 2.60 | 50.9% | |
| Damon Severson | D | 249 | 3.01 | 2.95 | 50.4% | |
| Denton Mateychuk | D | 283 | 2.43 | 2.58 | 48.5% | |
| Zach Werenski | D | 314 | 2.66 | 2.85 | 48.3% | |
| Ryan Lomberg | F | 117 | 1.93 | 2.09 | 48.0% | |
| Cole Sillinger | F | 204 | 2.82 | 3.08 | 47.9% | |
| Matthew Knies | F | 213 | 2.06 | 2.26 | 47.6% | |
| Kent Johnson | F | 204 | 2.20 | 2.53 | 46.5% | |
| Adam Fantilli | F | 235 | 1.99 | 2.38 | 45.5% | |
| Valeri Nichushkin | F | 200 | 2.34 | 2.82 | 45.4% | |
| Danton Heinen | F | 92 | 1.99 | 2.42 | 45.2% | |
| Erik Gudbranson | D | 154 | 1.54 | 2.16 | 41.6% | |
| Conor Garland | F | 181 | 1.89 | 2.84 | 40.0% | |
| Jake Christiansen | D | 180 | 1.78 | 2.70 | 39.8% | |
| Sean Monahan | F | 185 | 2.29 | 3.63 | 38.7% | |
| Dante Fabbro | D | 78 | 1.38 | 2.21 | 38.3% | |
| Carson Soucy | D | 93 | 1.71 | 2.90 | 37.1% | |
| Luca Del Bel Belluz | F | 61 | 1.45 | 2.38 | 37.8% | |
| Emil Andrae | D | 53 | 1.84 | 2.17 | 46.0% | |
| Jack Williams | F | 10 | 3.56 | 4.09 | 46.5% | |
| Steven Lorentz | F | 9 | 1.83 | 1.91 | 48.9% |
| Skater | Pos | TOI | xGF/60 | xGA/60 | xGF% | for / against |
|---|---|---|---|---|---|---|
| Valeri Nichushkin | F | 18 | 4.56 | 0.23 | 95.1% | |
| Denton Mateychuk | D | 17 | 4.51 | 0.25 | 94.7% | |
| Kent Johnson | F | 48 | 7.20 | 0.72 | 90.9% | |
| Charlie Coyle | F | 46 | 7.44 | 0.75 | 90.9% | |
| Sean Monahan | F | 21 | 6.27 | 0.70 | 90.0% | |
| Zach Werenski | D | 54 | 7.30 | 0.83 | 89.8% | |
| Adam Fantilli | F | 49 | 7.34 | 0.92 | 88.9% | |
| Matthew Knies | F | 48 | 7.03 | 0.94 | 88.3% | |
| Conor Garland | F | 19 | 4.41 | 0.77 | 85.2% | |
| Dmitri Voronkov | F | 9 | 4.69 | 0.47 | 90.9% | |
| Damon Severson | D | 6 | 3.35 | 0.03 | 99.2% | |
| Ivan Provorov | D | 5 | 2.44 | 0.00 | 100.0% | |
| Cole Sillinger | F | 5 | 4.73 | 0.00 | 100.0% | |
| Mathieu Olivier | F | 1 | 4.83 | 0.00 | 100.0% | |
| Dante Fabbro | D | 0 | 0.00 | 0.00 | — | |
| Erik Gudbranson | D | 0 | 0.00 | 0.00 | — | |
| Danton Heinen | F | 0 | 0.00 | 0.00 | — |
| Skater | Pos | TOI | xGF/60 | xGA/60 | xGF% | for / against |
|---|---|---|---|---|---|---|
| Jake Christiansen | D | 13 | 1.16 | 3.81 | 23.3% | |
| Cole Sillinger | F | 15 | 1.66 | 7.54 | 18.1% | |
| Damon Severson | D | 20 | 1.33 | 6.07 | 18.0% | |
| Danton Heinen | F | 9 | 0.18 | 2.11 | 7.7% | |
| Mathieu Olivier | F | 25 | 0.49 | 7.03 | 6.6% | |
| Valeri Nichushkin | F | 21 | 0.47 | 6.99 | 6.3% | |
| Charlie Coyle | F | 33 | 0.56 | 9.91 | 5.4% | |
| Zach Werenski | D | 33 | 0.64 | 11.99 | 5.1% | |
| Carson Soucy | D | 9 | 0.28 | 5.43 | 4.9% | |
| Denton Mateychuk | D | 24 | 0.24 | 8.78 | 2.6% | |
| Sean Monahan | F | 25 | 0.21 | 12.86 | 1.6% | |
| Erik Gudbranson | D | 27 | 0.00 | 13.53 | 0.0% | |
| Ivan Provorov | D | 7 | 0.15 | 14.83 | 1.0% | |
| Dante Fabbro | D | 7 | 0.00 | 3.80 | 0.0% | |
| Adam Fantilli | F | 6 | 0.00 | 10.46 | 0.0% | |
| Matthew Knies | F | 2 | 0.00 | 8.92 | 0.0% | |
| Conor Garland | F | 1 | 0.00 | 0.92 | 0.0% | |
| Jack Williams | F | 0 | 0.00 | 0.00 | — | |
| Luca Del Bel Belluz | F | 0 | 0.00 | 0.00 | — | |
| Kent Johnson | F | 0 | 0.00 | 0.00 | — |
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 CBJ 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 CBJ'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 CBJ 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.
Model estimates
🔒 5v5 · as of Jun 14, 2026Last 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.
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.
How it's built, and what it isn't
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.
Season context
season to dateFull table · all numbers
| Family | Stat | Value (current slice) |
|---|---|---|
| Observed ◆ filtered | Goals for / against | 25 / 28 |
| Observed ◆ filtered | xG for / against | 28.8 / 32.4 |
| Observed ◆ filtered | Shots for / against | 293 / 323 |
| Observed ◆ filtered | Attempts for / against | 646 / 685 |
| Modeled 🔒 5v5 | Shooting — our skaters · on our shots, vs this season's average | -0.1 G 47th pctl |
| Modeled 🔒 5v5 | Saving — our goalies · on shots faced, vs this season's average | +1.2 G 84th pctl |
| Modeled 🔒 5v5 | Shooting against — their skaters · on shots faced | -0.4 G 22nd pctl |
| Modeled 🔒 5v5 | Saving against — their goalies · on our shots | +0.2 G 78th pctl |
| Modeled 🔒 5v5 | Unadjusted xGF% | 47.0% |
| Modeled 🔒 5v5 | ↳ shooting shift | +1.05 pp |
| Modeled 🔒 5v5 | ↳ saving against shift | -0.81 pp |
| Modeled 🔒 5v5 | ↳ shooting against shift | -1.39 pp |
| Modeled 🔒 5v5 | ↳ saving shift | +1.85 pp |
| Modeled 🔒 5v5 | Adjusted xGF% | 47.7% 34th pctl |
| Context | Ice time — share by strength | +0.3 |
| Context | Score state — TOI by game state | trails a lot |
| Context | Goalie workload — starter's share of shots | 50% |
| Context | Schedule 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.