What is hockey analytics?

Hockey analytics means using structured data — shot attempts, expected goals, ice time, zone plays and matched player IDs — to support decisions that traditional box scores alone cannot. At The Hockey Analytics it also means delivering those readings as scoped projects for clubs, media and scouts.

What is the difference between Corsi and xG?

Corsi counts all shot attempts equally (volume / territorial proxy). Expected goals (xG) weights each shot by estimated scoring chance. High Corsi with low xG often means perimeter volume without danger.

Where can clubs buy custom hockey analytics from THA?

Email to scope a package on /for-teams — single question, deep dive, season partner, or WiseHockey / InStat integration. Public example analyses live under /analyses.

Concepts

Hockey analytics glossary

Short definitions of the hockey analytics terms clubs, coaches, scouts and media actually use. Conceptual — not a promise of every model variant. For buying analytics work, see services for teams.

Hockey analytics: Using repeatable hockey data (shots, expected goals, ice time, zone plays, salaries where public) to answer decisions — recruitment, usage, opponent prep, storytelling — instead of relying only on goals and points.
Expected goals (xG): Each shot gets a 0–1 probability of becoming a goal based on factors such as location, shot type, traffic and game situation. Team or player xGF% is the share of expected goals for versus against while on ice.
Corsi (CF%): All shot attempts: shots on goal, misses and blocks. CF% is the share of those attempts for versus against. A volume and zone-time proxy that can diverge from xG when shots come from low-danger areas.
Fenwick (FF%): Like Corsi but excluding blocked shots — unblocked shot attempts only. Some analysts prefer it when blocking rates differ by system.
GSAX (goals saved above expected): Goaltender measure: actual goals against compared with expected goals against from shot quality faced. Positive GSAX means the goalie prevented more goals than an average goalie on the same shots.
PDO: On-ice shooting percentage plus on-ice save percentage. League average sits near 100; extreme PDO often regresses as finishing and save luck even out.
High-danger chances: Shots from the highest-probability areas (typically slot / crease). A subset of the quality signal that xG models also capture.
Zone entry / exit: How a team enters or leaves the offensive or defensive zone (carry, dump, pass). Controlled entries usually create better shot quality than dump-ins.
WiseHockey / Wise Hockey: Club-owned tracking used by many European organisations. THA integrates WiseHockey feeds only inside consulting engagements; that data stays private to the client and is not mixed into public example analyses.

FAQ

What is hockey analytics?: Hockey analytics means using structured data — shot attempts, expected goals, ice time, zone plays and matched player IDs — to support decisions that traditional box scores alone cannot. At The Hockey Analytics it also means delivering those readings as scoped projects for clubs, media and scouts.
What is the difference between Corsi and xG?: Corsi counts all shot attempts equally (volume / territorial proxy). Expected goals (xG) weights each shot by estimated scoring chance. High Corsi with low xG often means perimeter volume without danger.
Where can clubs buy custom hockey analytics from THA?: Email to scope a package on /for-teams — single question, deep dive, season partner, or WiseHockey / InStat integration. Public example analyses live under /analyses.

Ask your hockey question