Time on ice competition plots for all 30 teams
Eric T.
August 17 2012 07:26AM
Duncan Keith had a negative Corsi Rel last year, but he's not weak competition
By Matt Boulton from Vancouver, Canada (Kane, Keith and Kopecky) [CC-BY-SA-2.0 (http://creativecommons.org/licenses/by-sa/2.0)], via Wikimedia Commons
Yesterday, we published an article about evaluating quality of competition by looking at the opponents' average time on ice. The best players typically see the most ice time, so a player whose opponents get a lot of minutes is probably facing tough competition. By this metric, top-line forwards appeared to face tougher competition than is suggested by other metrics.
The reason for this became clear when we separated out the quality of forwards and defensemen that a player faced. Even the offense-first forwards who are used against mediocre competition see their opponents' best defensemen. This opened up the interesting possibility of using quality of competition to evaluate not just the strength of the competition, but the type of situations -- facing good forwards and bad defensemen might be similar in difficulty to facing bad forwards and good defensemen, but it is a very different type of usage.
We showed a couple of examples, one from a team that matched their top forwards with the opposition's top forwards, and one from a team that had an offense-first scoring line and a defensive-minded shutdown line. A number of people inquired about their favorite team, so we decided to publish plots for each of the 30 teams for 2011-12.
A competition metric based on ice time
Eric T.
August 16 2012 07:49AM
Daniel Sedin facing a top-flight defenseman, as always
By kcxd (Canucks!) [CC-BY-2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons
Our traditional quality of competition metrics aim to answer the question "how tough was this player's competition?"
To do that, they start by assigning each player some kind of score to assess how tough an opponent he is; then to calculate a player's quality of competition, you average his opponents' scores together. There are a variety of choice for what score you use -- one metric uses the team's shot differential with that player on the ice, another looks at how the team's shot differential changed when he stepped on the ice.
Each of those scores has certain weaknesses, and the stat community recognizes that none of them can be used as a single metric to rank players and declare someone to be the best in the league. Yet in essence, that's what the quality of competition metrics do.
A little over a year ago, a group of analysts was asked what stats they turn to first. Such leaders in the field as Gabe Desjardins, Jonathan Willis, and Tom Awad all said that if they only get one stat, they're going to look at ice time.
It makes sense -- a player's ice time is a direct reflection of the coach's opinion of the player, and at this relatively early stage in the evolution of analytics, the coach's opinion is more accurate than any one individual statistic.
So why not try to build a quality of competition metric using ice time as the measure of how good each opponent is? Let's try it.
Almost famous: Lessons from a near miss
Eric T.
August 07 2012 06:19AM
The universe - it's not so static.
Photo by NASA, Public Domain
It was one of those moments that you live for in research. A shocking result popped out of the analysis. "Holy crap, this is going to change the game," I thought.
But that's not the story here. The real story is what happened next.
Projections for Rick Nash on the Rangers
Eric T.
July 30 2012 07:23AM
By 5of7 (Rick Nash), via Wikimedia Commons
Corey has already laid out some Rick Nash facts. Now that we know where he'll be playing next year, I'm going to take a stab at projecting how his production might change if he is on a line with Brad Richards.
To do that, I'll make estimates at how much the following factors might adjust his performance up or down from last year:
- How much more (or less) ice time will he get? (Affects goals and assists)
- How many more (or fewer) shots will his new line generate? (Affects goals and assists)
- How did last year's shooting percentage compare to his established career performance? (Affects goals)
- How should we expect his new linemates to affect his shooting percentage? (Affects goals)
- How much better (or worse) are his new linemates' shooting percentages? (Affects assists)
- How will his power play production change? (Affects goals and assists)
Obviously this will require some guesswork, and I'm not arguing that the season will play out exactly according to my arithmetic, but working through the results in this manner gives us a good baseline expectation for what is reasonable and for how important each of these factors is. Let's see where it takes us.
The importance of quality of competition
Eric T.
July 23 2012 09:11AM
Abstract
Quality of competition faced is often used qualitatively when assessing a player’s performance, but a quantitative adjustment has proven elusive. It has been widely presumed that the difficulty arises from stratification of playing time; if the players who face top competition are usually themselves good players, then we would not see facing top competition correlating with poor results.
