2014-15 vs 2013-14 Rush Shots and shooting/save percentages

I have mentioned on twitter how I was looking at rush shots as a percentage of overall shots and how teams have fared compared to last season. Here is how the teams have done from an offensive perspective. Team RushShot% For Diff Sh% Diff NY Rangers 7.24% 2.47% Arizona 6.07% 0.92% San Jose 5.89% -0.01% Edmonton 5.64% -1.23% Buffalo 5.02% 2.70% Washington 3.64% 0.65% Anaheim 3.10% -2.09% Calgary 2.83% -0.33% Pittsburgh 2.71% 0.72% Columbus 2.51% -0.23% New Jersey 2.37% 1.57% Vancouver 2.31% 1.32% Winnipeg 2.21% -1.71% Montreal 1.52% -0.11% Los Angeles 1.43% 1.09% Minnesota 1.21% 1.12% St. Louis 1.20% -1.16%

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Why zone starts don’t matter much

I have written a number of posts on zone starts and how they don’t generally have a significant impact on a players overall statistics but I constantly run across people that find that difficult to accept. There are still studies being done looking at how long the impact of a zone start has on outcomes (this was based on some of the work of Tyler Dellow). While these are interesting studies, the important thing to understand is that while there is an impact it has relatively little impact on a players overall statistics. Before Tyler Dellow was hired by the Edmonton

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Estimating Standard Deviation in On-ice Shooting Percentage Talent

I have tackled the subject of on-ice shooting percentage a number of times here but I think it is a subject that has been under researched in hockey analytics. Historically people have done some split half comparisons found weak correlations and written it off as a significant or useful factor in hockey analytics. While some of the research has merit, a lot of the research deals with too small of a sample size to get any really useful correlations. Split-half season correlations with majority of the players is including players that might have 3 goals int he first half and

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Goals, Corsi, and Weighted Shot Differential

Yesterday ‘Tangotiger’ introduced a new hockey metric that got the hockey twitter world all excited. Go read the articles for the methodology and rational behind the metric but in short he conducted first half season vs second half season regression and discovered that goals and shot attempts that didn’t result in goals should be weighted differently. The final result was that for his weighted shot differential goals should be given a weight of 1.0 and shot attempts that didn’t result in goals (saved, missed the net or blocked) should be given a weight of 0.2. Although he concluded that because

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Does higher Corsi Against rates boost Save Percentage?

Yesterday I wrote an article for MapleLeafsHotStove.com looking at the Leafs performance so far this season in comparison to previous seasons. In it I showed a chart comparing the Leafs CA/60 rate in comparison with their Save% and it was quite astonishing how they rose and fell in lock-step. Here is that chart:   Very rarely in hockey analytics do you get a chart that looks as “nice” as that one so it is something that really draws my attention. Essentially what this is saying is that the more shot attempts you give up the higher the goalies save percentage

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Boosting save percentage…

Last night on twitter I posted some GF%RelTM statistics which resulted in a number of comments but notably some from Stephen Burtch about how players cannot be blamed for GF% and is nothing more than a fancy +/- stat and how players can’t be blamed or given credit for things such as save percentage. @hockeyanalysis @mlse Polak .910 on-ice sv% at 5v5 close past 4 years. Robidas .905 on-ice sv%. We should totally blame them. — Stephen Burtch (@SteveBurtch) September 26, 2014 .@hockeyanalysis @mlse Carl Gunnarsson had a .926 5v5 close on-ice sv% which was totally caused by his skill.

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Relative importance of Corsi and the other 42%

Today apparently there was some discussion about the Avalanche and their non-interest in hockey analytics. In that discussion Corey Pronman wrote the following tweet: @ThomasDrance @adater point is Corsi explains 35% of wins. Luck explains about 40%. If something’s better than Corsi, not much room left. — Corey Pronman (@coreypronman) September 24, 2014   I have seen the above logic from time to time. I think it dates back to something Gabe Desjardins wrote many years ago. I find the logic very odd though. Let me explain. Let’s assume that the numbers are true. According to my math, that leaves

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Evaluating defensive ability

A short while ago I aksed the question of who the best defensive defensemen in the NHL are to my twitter followers and it became clear to me that I am not certain people really know how to evaluate players defensive ability. I’ll explore that further in a bit but first here are some of the answers I received. Vlasic Seabrook Chara Muzzin Fayne Giordano Stralman Andy Greene Rozsival Paul Martin Shea Weber Hjalmarsson Phillips and probably a few more I missed It also spawned a lot of talk about corsi%, CorsiRel and players CF% with and without certain players. This really

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TSN Analytics Team, Even Strength Play and Marc-Edouard Vlasic

Earlier this week TSN announced the creation of an Analytics team consisting of long-time TSN contributor Scott Cullen along with new TSN additions of Globe and Mail’s James Mirtle and hockey blogger Travis Yost. I am all for main stream media jumping on board with hockey analytics but once you go from independent hockey blogger to a significant contributor to TSN I think it opens the door to higher expectations and higher standards.  Scott Cullen has a long track record with TSN and I am confident James Mirtle will bring some intelligent insight as we are all familar with and respect his

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Team Zone Entry Data and Predicting Standings

I am sure many of you are aware that Corey Sznajder (@ShutdownLine) has been working on tracking zone entries and exits for every game from last season. A week and a half ago Corey was nice enough to send me the data for every team for all the games he had tracked so far (I’d estimate approximately 60% of the season) and the past few days I have been looking at it. So, ultimately everything you read from here on is thanks to the time and effort Corey has put in tracking this data. As I have alluded to on

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