Jump to content

About This Club

Reference and discussion place for any and all analytic and predictive computational tools used in hockey analysis, whether they be raw, adjusted, derived, or processed.


United States
  1. What's new in this club
  2. For reference: There are statistics that teams can keep and people measure which may or may not be useful. I have no problem with someone having their own numbers to track that s/he thinks are useful. However, the most common advanced stats are that common for pretty good reasons: they are easy to measure and serve as a solid proxy for important parts of the game that correspond to winning. As we noted, based on simple raw numbers and on the most common advanced stats, there was no excuse for Botterill to have wasted Pegula's money on Frolik and Simmonds, let alone have Thompson a
  3. I figure this is like this tracking the stock market and such. You can't track everything, so you try to determine what the most relevant facts are that you can easily collect. Then you make a model using whatever methods are relevant and at your disposal. Aside on modelling - When I took engineering modelling in college, my prof explained models this way: You can have several models of a tree. You can have a pre-schooler draw a tree which has a brown or grey trunk and a tuft of green that is supposed to be the leaves. You then have that of an amateur artist which has the rai
  4. Charts and graphs have become ubiquitous here at SabreSpace, which is fine, but people seem to have a blind faith in their accuracy. With the amount of data being collected, how is it done and by whom? Are there firms with twenty or so employees sitting around, rewinding playback machines with stopwatches in their hands working for each team? To me, it seems like it would take one person an entire day, if not more, to analyze a a single aspect of a single game. Just wondering.
  5. These are the fun stats, where we can measure greatness and incompetence. Many of these have obvious variations which I will not bother to enumerate here. Team Devastation Rating (good teams): Team Goal Differential / League Average Goal Differential Team Devastated Rating (bad teams): League Average Goal Differential / Team Goal Differential Individual Player Presence (think of this as "lone wolf" situations): rate of stat when player is on the ice / team's rate of stat without that player on the ice. So when you see that the Sabres' numbers all congregate in a tiny area
  6. Crucial Situations Originally Created: Early 1980s Creators: Roger Nielson, Al Arbour, Emile Francis, Jeff Z. Klein, Karl Eric-Reif, writers for the old hockey annuals Inspiration: Find out who the Joe Schlabotniks are who score goals in borderline irrelevant situations, make spectacular saves when the game is out of hand, etc. Logic: Track who is making key plays that preserve leads or tie games How to Measure It: What you measure and how you use it varied wildly from statistician to statistician. I will concentrate on tying or go-ahead goals, although you can do a l
  7. Adjusted Plus-Minus Originally Created: Late 1970's Original Creators: Lou Nanne, Emile Francis, and others Inspiration: Try to get players on good teams and bad to be measured on the same relative two-way scale. Logic: How do we determine players on bad teams who are actually performing well, but are dragged down by lousy team-mates? Conversely, who on good teams is actually performing poorly because his team-mates inflate his raw numbers? How to compute it: There were actually 3 versions of this stat. Original Background: Easiest
  8. Goaltender Perseverance ratings: (Save pct *6 + average shots against / game) / 0.6 Created: 1981 Creators: Hockey News Writers Jeff Z. Klein and Karl-Eric Reif Inspiration: Avoid using GAA for comparing goaltenders because good goaltenders on bad teams look worse than bad goaltenders on good teams. Logic: Save Percentage is generally a more predictable long-term, team-independent statistic than GAA. Add in the shots against per game to measure workload; thus the same save percentage for a goaltender on a weaker team that surrenders more shots will show a higher perseveran

  • Create New...