In a field that loses value with subjective interpretation of events, the ability to provided consistent objective measurement is key.
Below is how we define events in the context of data collection.
Time on Ice
TOI: Total amount of ice time for every game situation (Even-Strength/Powerplay/Penalty Kill)
PP: Total amount of ice time on the Powerplay
PK: Total amount of ice time on the Penalty Kill
Shifts: How many shifts the player plays, used to find average shift length
Seconds Played: Used for Pass/60min and Point/60min calculations, etc.
When Bill James started looking at numbers in baseball, it was not for the sake of numbers themselves but the stories they tell.
Everyone knows the often misappropriated saying of “lies, damn lies, and statistics” with how an individual can manipulate numbers by ignoring what does not fit. Numbers are no different than stories: people can see what they want to see if they try hard enough. However, numbers and stories are necessary in understanding what happened and making more informed, and therefore potentially better, decisions.
The game of hockey is a goal scoring contest; the team with the most goals wins. It can be broken down to it’s individual events like shots, penalties, hits, passes, and hits to gain a better understanding of what is going on.From this we can better understand how events relate to the teams and players that best drive wins, like we do here at HockeyData with numbers like our own THP.