Utah Mammoth
5-on-5 · model-estimatedMammoth: a outshot/run-and-gun team (0.0% 5v5 xG) with league-average goaltending.
How to read this
This is one team through the publication's three layers. The identity row separates process — the chances a club creates and allows (, ) — from luck, which is what measures. Process predicts the future; luck predicts a correction.
Everything below follows that split: regression flags mark places where results have outrun (or trailed) the underlying play, talent tiers and the player table rank the roster by a model-estimated , and roster needs compare each position group against league average. The proxies rank things usefully but share credit with linemates — read orderings as solid and exact magnitudes as approximate.
- PROCESS
- chance creation and possession — xG%, Corsi. The repeatable part.
- RESULT
- goals, wins, special-teams conversion. What the standings see.
- LUCK
- PDO, finishing vs expected, GSAx — the part that mean-reverts.
- GOLD/RED
- regression flags: gold = watch it, red = act on it
- WAR / Impact are model-estimated proxies, not cap-validated
- Roster-need gaps are ordinal — ranked correctly, magnitudes relative
- No standout edges flagged.
- Out-chanced at 5v5 (0.0% xG share).
- Leaky penalty kill (78% kill rate).
- None
- Clayton Keller
- Dylan Guenther
- Nick Schmaltz
- Lawson Crouse
- Logan Cooley
- John Marino
- Michael Carcone
- Nate Schmidt
- Kailer Yamamoto
- Barrett Hayton
- Ian Cole
- Nick DeSimone
- Daniil But
- JJ Peterka
- Mikhail Sergachev
- Sean Durzi
- Jack McBain
- Alexander Kerfoot
- MacKenzie Weegar
- Liam O'Brien
- Dmitri Simashev
- Brandon Tanev
- Kevin Stenlund
Special teams
Goaltending
| Goaltender | GP | |||
|---|---|---|---|---|
| Karel Vejmelka | 64 | 89.670 | — | +0.0 |
| Vitek Vanecek | 22 | 88.340 | — | +0.0 |
Gaps are ordinal — needs are ranked correctly; treat the magnitude as relative, not absolute.
| Player | GP | TOI/GP | ||
|---|---|---|---|---|
| Clayton KellerR | 82 | 14.9 | +70.60 | +4.0 |
| Dylan GuentherR | 79 | 13.2 | +74.50 | +3.7 |
| Nick SchmaltzC | 82 | 14.3 | +67.30 | +3.4 |
| Lawson CrouseL | 81 | 12.4 | +69.70 | +2.3 |
| Logan CooleyC | 54 | 13.7 | +74.30 | +2.2 |
| JJ PeterkaR | 82 | 13.7 | +56.60 | +2.1 |
| John MarinoD | 80 | 17.9 | +69.10 | +1.7 |
| Mikhail SergachevD | 78 | 17.3 | +47.80 | +1.7 |
| Michael CarconeL | 79 | 11.6 | +70.00 | +1.7 |
| Nate SchmidtD | 82 | 16.7 | +74.00 | +1.5 |
How hard is this team’s season, logistically? This grades the schedule itself — travel, rest, and clustering — separate from how good the team is.
Schedule load
The 14th-heaviest schedule in the league — 84 games, 1.3 days average rest.
Nights of rest before each game · 0 days = red, 3+ = green
21 games with more rest than the opponent · 22 with fewer · 40 even.
6 games in 10 days with 5,201 travel miles
Feb 12 – Feb 21
6 games in 9 days with 2,674 travel miles
Nov 25 – Dec 3
6 games in 12 days with 5,127 travel miles
Feb 26 – Mar 9