NHL Analytics Glossary

Graphic: SportTechie

The following analytics glossary is divided into three primary categories:

  • Possession
  • Quality of Chances
  • Player Value


POSSESSION


Corsi

  • Corsi For (CF): Any shot attempts made by a player in the course of a game while the player is on the ice. Corsi shot attempts differ from the basic shots on goal (SOG) stat because they include any/all shot attempts, regards if the shot is on goal or blocked.
  • Corsi Against (CA): Any shot attempts allowed by a team for players on the ice.
  • Corsi For Percentage (CF%): The total of Corsi For shot attempts divided by the total of Corsi For shot attempts and Corsi Against shot attempts. A player percentage over 50% indicates his team is generating more shot attempts than the opposition when the player is on the ice.

Fenwick

  • Fenwick For (FF): Unblocked shot attempts made by a player in the course of a game while a player is on the ice.
  • Fenwick Against (FA): Unblocked shot attempts allowed by a team for players on the ice.
  • Fenwick For Percentage (FF%): The total of Fenwick For shot attempts divided by the total of Corsi For shot attempts and Corsi Against shot attempts.

Differences Between Corsi and Fenwick

  • Corsi shot attempts are any shot attempt in the offensive zone, including shots that are on goal, shots that miss the net, or shots that are blocked.
  • Fenwick shot attempts are shot attempts in the offensive zone that are shots on goal or shots that miss the net. Fenwick does not include blocked shot attempts.

QUALITY OF CHANCES


Expected Goals

  • Expected Goals For (xGF): A statistic that weighs a shot attempt or scoring chance with the likelihood of a goal being scored. The stat correlates a specific shot attempt location with conversion rates based on historical data from that specific shot location.
  • Expected Goals Against (xGA): A statistic that weighs a shot attempt or scoring chance allowed with the likelihood of a goal being scored.
  • Expected Goals Percentage (xGF%): The total of Expected Goals For divided by the total of Expected Goals For and Expected Goals against

High, Medium, and Low Danger Chances

  • High Danger Chance For (HDCF): A scoring chance that is highly likely to result in a goal scored for a team.
  • High Danger Chance Against (HDCA): A scoring chance allowed that is highly likely to result in a goal scored for the opposing team.
  • High Danger Chance For Percentage (HDCF%): The total of High Danger Chances For divided by the total of High Danger Chances For and High Danger Chances Against
  • Medium Danger Chance For (MDCF): A scoring chance generated that is somewhat likely to result in a goal scored for a team.
  • Medium Danger Chance Against (MDCA): A scoring chance allowed that is somewhat likely to result in a goal allowed by a team.
  • Medium Danger Chance For Percentage (MDCF%): The total of Medium Danger Chance For divided by the total of Medium Danger Chance For and Medium Danger Chance Allowed.
  • Low Danger Chance For (LDCF): A scoring chance generated that is relatively unlikely to result in a goal scored.
  • Low Danger Chance Against (LDCA): A scoring chance allowed that is relatively unlikely to result in a goal scored.

High, Medium, and Low Danger Goals Scored

  • High Danger Goals For (HDGF): A goal scored as a result of a high danger chance generated.
  • High Danger Goals Against (HDGA): A goal allowed as a result of a high danger chance against.
  • High Danger Goals For Percentage (HDGF%): The total of High Danger Goals For divided by the total of High Danger Goals For and High Danger Goals Against.
  • Medium Danger Goals For (MDGF): A goal scored as a result of a medium danger chance generated.
  • Medium Danger Goals Against (MDGA): A goal allowed as a result of a medium danger chance.
  • Medium Danger Goals For Percentage (MDGF%): The total of Medium Danger Goals For divided by the total of Medium Danger Goals For and Medium Danger Goals Against.
  • Low Danger Goals For (LDGF): A goal scored as a result of a low danger chance.
  • Low Danger Goals Against (LDGA): A goal allowed as a result of a low danger chance.
  • Low Danger Goals For Percentage (LDCF%): The total of Low Danger Goals For divided by the total of Low Danger Goals For and Low Danger Goals against.

PLAYER VALUE


Goals Above Replacement (GAR):

A multi-faceted metric that provides an insight to overall player value against a replacement level player (a player outside the normal 13 forwards or 7 defensemen on a given NHL roster). GAR takes into account several sub-metrics, which include:

  • Even-Strength Offense GAR (EVO): A measurement of how a player stacks up to other players in the same position group regarding offensive production at even strength.
  • Even-Strength Defense GAR (EVD): A measurement of how a player stacks up to other players in the same position group regarding defensive production at even strength
  • Power Play Offense GAR (PPO): A measurement of how a player stacks up to other players in the same position group regarding offensive production on the power play.
  • Shorthanded Defense GAR (SHD): A measurement of how a player stacks up to other players in the same position group regarding defensive production on the penalty kill.
  • Penalties Taken GAR (Take): A measurement of how a player stacks up to other players in the same position group regarding how many penalties a player takes. The fewer penalties a player takes, the better their Penalties Taken GAR.
  • Penalties Drawn GAR (Draw): A measurement of how a player stacks up to other players in the same position group regarding how many penalties they draw. The more penalties they draw from their opponents, the higher their Penalties Drawn GAR.
  • Offensive GAR (oGAR): A combination of a player’s Even-Strength Offense GAR and Power Play Offense GAR.
  • Defensive GAR (dGAR): A combination of a player’s Even-Strength Defense GAR and Shorthanded Defense GAR.
  • Penalties GAR (Pens): A combination of Penalties Taken GAR and Penalties Drawn GAR.
  • For more information on how GAR is calculated, please visit Evolving-Hockey’s article here.

Quality of Competition and Teammates:

  • Quality of Competition (QoC): A metric that tracks the quality of the defensemen a forward faces or the quality of the forward a defenseman faces when on the ice.
  • Quality of Teammates (QoT): A metric that tracks the quality of teammates that are on the ice at the same time as the player in question.

Regularized Adjusted Plus-Minus (RAPM)

RAPM is based off a popular metric used to evaluate a player’s talent level in basketball. Effectively, RAPM is used to compare a player’s performance in key statistical areas, mainly goals for, expected goals for, Corsi for, expected goals against, and Corsi Against. The way that these key metrics become “rate adjusted” is by finding the rate per sixty minutes of play that a player performs in these metrics.

For the RAPM charts that are commonly used in our posts (via Evolving-Hockey), the rates at which the players perform in these key metrics are displayed in a bar graph format. These charts do not show the actual production rates or figures the player performs, but how they stack up to the positional averages for each of these metrics, effectively forming a baseline for measuring whether a player is performing above or below their positional average in those metrics.

For more in depth information on how RAPM is calculated, please visit Evolving-Hockey’s glossary. They are essentially the experts in calculating RAPM, and definitions on how RAPM is formulated and calculated are heavily reliant on their glossary. For more history on how RAPM came to be used in hockey, here’s an article on Hockey-Graphs.com.

About Justin Trudel

Justin is a lifelong Caps fan, with some of his first memories of the sport watching the team in the USAir Arena and the 1998 Stanley Cup appearance. Now a resident of St. Augustine, FL, Justin watches the Caps from afar. Justin graduated with a Bachelor's of Science in Political Science from Towson University, and a Master's of Science in Applied Information Technology from Towson University. Justin is currently a product manager at a non-profit in Jacksonville, FL. Justin enjoys geeking out over roster construction and cap management.
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