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Understanding hockey analytics can seem daunting at first, but breaking it down into manageable concepts can make it more accessible for beginners. Here’s a beginner’s guide to understanding hockey analytics:
1. What Are Hockey Analytics?
- Hockey analytics involve the use of statistical analysis to evaluate player and team performance, identify trends, and gain insights into various aspects of the game.
2. Key Metrics:
- Corsi: Corsi measures shot attempts (shots on goal, missed shots, and blocked shots) for and against a team while a player is on the ice. It provides an indication of puck possession and offensive pressure.
- Fenwick: Similar to Corsi but excludes blocked shots. Fenwick focuses on shots on goal and missed shots, providing a more accurate measure of shooting proficiency.
- Expected Goals (xG): xG quantifies the quality of scoring chances based on factors such as shot location, angle, and type. It helps assess a team’s ability to generate high-quality scoring opportunities.
- Zone Entries/Exits: Analyzing how teams enter and exit the offensive and defensive zones can provide insights into puck possession, transition play, and offensive strategy.
- Zone Starts: Zone starts refer to the location on the ice where a player begins a shift. Analyzing zone starts can help evaluate coaching strategies, player deployment, and defensive responsibilities.
3. Advanced Metrics:
- PDO: PDO combines a team’s shooting percentage and save percentage to assess whether their current performance is sustainable or influenced by luck. A PDO around 100 is considered average.
- Relative Metrics: Metrics such as Corsi For Percentage (CF%) and Expected Goals Percentage (xGF%) compare a player’s performance to that of their teammates or opponents. Positive values indicate a player’s positive impact on play.
- Zone Adjusted Metrics: Adjusting analytics based on zone starts or quality of competition provides a more accurate assessment of a player’s performance in different situations.
4. Practical Applications:
- Player Evaluation: Analytics help assess player contributions beyond traditional statistics like goals and assists. They reveal players who excel in driving possession, creating scoring chances, or suppressing opponent offense.
- Team Strategy: Coaches use analytics to optimize line combinations, defensive pairings, and in-game tactics based on data-driven insights. Analytics inform decisions regarding offensive systems, defensive schemes, and special teams play.
- Player Development: Analytics assist in player development by identifying areas for improvement and tracking progress over time. Coaches and players can focus on enhancing performance in specific aspects of the game.
5. Resources for Learning:
- Websites: Explore websites like Natural Stat Trick, Evolving-Hockey, and Hockey Graphs for in-depth analytics articles, glossaries, and interactive tools.
- Books: Books such as “Hockey Abstract” by Rob Vollman and “Stat Shot” by Rob Vollman and Tom Awad offer comprehensive insights into hockey analytics for beginners and advanced enthusiasts alike.
