Tampa Bay Lightning
5-on-5 · model-estimatedLightning: a outshot/run-and-gun team (0.0% 5v5 xG) with league-average goaltending, flagged for regression (1 signals).
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
- Elite top-end talent: Brandon Hagel, Darren Raddysh, Anthony Cirelli.
- Out-chanced at 5v5 (0.0% xG share).
PDO 1.019 — running hot at 5v5; expect negative regression.
Flags mark gaps between process and result likely to move toward the mean.
- Brandon Hagel
- Darren Raddysh
- Anthony Cirelli
- J.J. Moser
- Ryan McDonagh
- Nikita Kucherov
- Jake Guentzel
- Charle-Edouard D'Astous
- Gage Goncalves
- Pontus Holmberg
- Max Crozier
- Brayden Point
- Corey Perry
- Yanni Gourde
- Dominic James
- Erik Cernak
- Zemgus Girgensons
- Nick Paul
- Emil Lilleberg
- Oliver Bjorkstrand
- Victor Hedman
- Declan Carlile
Special teams
Goaltending
| Goaltender | GP | |||
|---|---|---|---|---|
| Andrei Vasilevskiy | 58 | 91.230 | — | +0.0 |
| Jonas Johansson | 25 | 88.360 | — | +0.0 |
Gaps are ordinal — needs are ranked correctly; treat the magnitude as relative, not absolute.
| Player | GP | TOI/GP | ||
|---|---|---|---|---|
| Nikita KucherovR | 76 | 15.0 | +73.50 | +5.7 |
| Brandon HagelL | 71 | 14.2 | +85.50 | +4.2 |
| Jake GuentzelC | 81 | 14.0 | +74.20 | +4.1 |
| Darren RaddyshD | 73 | 17.1 | +82.70 | +3.7 |
| Anthony CirelliC | 71 | 12.6 | +79.30 | +2.8 |
| J.J. MoserD | 79 | 18.1 | +79.10 | +1.9 |
| Brayden PointC | 63 | 13.7 | +56.10 | +1.9 |
| Charle-Edouard D'AstousD | 70 | 16.6 | +74.30 | +1.6 |
| Gage GoncalvesC | 74 | 11.7 | +60.00 | +1.5 |
| Ryan McDonaghD | 48 | 15.4 | +86.30 | +1.4 |
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 5th-heaviest schedule in the league — 84 games, 1.3 days average rest.
Nights of rest before each game · 0 days = red, 3+ = green
25 games with more rest than the opponent · 12 with fewer · 46 even.
6 games in 10 days with 4,933 travel miles
Feb 27 – Mar 8
6 games in 9 days with 3,600 travel miles
Dec 12 – Dec 20
6 games in 10 days with 3,821 travel miles
Nov 5 – Nov 14