League Efficiency
Who is actually controlling games, and who is just getting the bounces? Every team plotted by shot volume against shot quality at 5-on-5 — then the PDO watch: the teams whose results are running ahead of, or behind, their process.
How to read this
Two questions, one page. First: when a team is on the ice, does it out-attempt the opponent (), and do those attempts turn into dangerous chances ()? Teams above 50% on both are genuinely tilting the ice. Teams with volume but no quality are spraying the outside — the scoreboard usually catches up to them.
Second: — shooting percentage plus save percentage. It clusters hard around 1.000 league-wide, so a team far above it is getting hot goaltending or hot sticks that history says won't last, and a team far below it is better than its record. Read the extremes as candidates for regression, not verdicts.
- CF%
- share of all shot attempts — pure volume
- xG%
- share of expected goals — chance quality
- SH%
- team shooting percentage at 5-on-5
- SV%
- team save percentage at 5-on-5
- PDO
- SH% + SV% — league average ≈ 1.000
- MoneyPuck team CSV · 5-on-5 · 32 teams · revalidated hourly
- 2025–26 rates — the 2026–27 sample isn't live yet
2025–26 rates — the 2026–27 sample isn't live yet
Shot volume vs. shot quality
X is shot-attempt share (volume), Y is expected-goal share (quality). Teams above the diagonal convert attempts into dangerous chances; teams below it pile up attempts the model doesn't believe in.
is the puck-luck meter. Teams far from 1.000 almost always drift back: the hot ones cool off (sell high), the cold ones bounce back (buy low). The xG% column says whether the underlying process backs the record up.