Hockey is all about speed, skill, and coordination from its inception. But now, it is not only a form of artistry but is full of mathematics. Over the years, statistics in hockey have become quite popular among the players, as they rely on data to analyze their colleagues, develop new tactics, and have the upper hand on the field.
This article will explain what hockey analytics is and how it’s changing the sport. This knowledge can directly be put into practice at the gaming giant Woo Casino. Thousands visit every day to have friendly battles and receive big rewards along the way!
What Is Hockey Analytics?
Hockey analytics means using data to study the game and looking deeper than basic stats like goals and assists. Teams analyze advanced metrics to understand performance, strategies, and more.
For example, traditional stats tell you how many goals an athlete scored and advanced stats, like “expected goals” (xG), tell you how likely a shot is to result in a goal. This shows who has the best scoring chances.
Why Are Analytics Important?
Analytics help teams make smarter decisions. Coaches can use it to:
- Improve strategy: It can show which plays work best or which areas of the ice are most dangerous.
- Evaluations: Data can highlight who contributes in ways that might not show up on a scoresheet.
- Predict outcomes: Teams use it to find trends that could predict future performance.
Key Terms
If you’re new to this, some terms might sound confusing. Here are a few of the most common ones:
- Corsi: Measures shot attempts (shots on goal, missed shots, and blocked shots). It shows which team controls the puck more.
- Fenwick: Like Corsi, but doesn’t count blocked shots.
- Expected Goals (xG): Predicts how many goals an individual or unit should score based on shot quality.
- Zone Entries/Exits: Tracks how often someone successfully moves the puck in or out of a zone.
- PDO: Combines a team’s shooting percentage and save percentage. It can show if they are lucky or unlucky.
These stats give teams a clearer picture of what’s happening on the ice.
How Do Teams Use This?
Every NHL team now has an analytics department, and here are some of the ways they can be used:
- Player Evaluation: Teams look for those who fit their system, and these stats help identify underrated faces who might not score much but have a solid defense or create scoring chances for teammates.
- Draft Decisions: Analytics help units find young talent with the most potential, by using this pool of information to predict which prospects will succeed in the NHL.
- In-Game Strategy: Coaches employ information throughout a game; for example, if a certain group is finding it difficult to contain zone entries, the coach may change tactics immediately.
- Injury Prevention: They are now able to monitor how intensively someone skates and how long they have been on the ice so that they do not over-exhaust themselves or the blades.
How It Changed Strategy
Hockey strategy has evolved because of this, as teams are now:
- Focusing on puck possession: Stats like Corsi show that crews with more puck possession win more often, so coaches emphasize keeping the puck rather than dumping it into the offensive zone.
- Taking smarter shots: Numbers reveal that shots from certain areas, like the slot, are likelier to score, so high-quality scoring chances should be the focus.
- Using better line combinations: Information shows which constellations perform best together, which creates effective lineups.
Examples & Critique
One famous example is the Toronto Maple Leafs when they hired Kyle Dubas as general manager (who was a strong supporter of this method). Under his leadership, they became one of the NHL’s top offensive crews.
Yet, not everyone loves basing everything on numbers, as some think it takes the emotion out of the game and others say it’s hard to measure intangible factors, like leadership or “hockey sense.”
