Past Studies Done Here (Links Only)
This is meant to be a resource where posters may:
- post links to and the results of studies which utilize the mathematical analysis of hockey data and statistics
- access the variety of studies which may be presented here
If you wish to give substantial feedback on a particular study, please do so in the thread for that study or on the general discussion thread located here:
If you do not value these studies in general and/or any specific study, then this is not the place to show your lack of appreciation. Non-constructive criticism may be deleted by the moderators.
It might be best for the authors of studies to use their first (or one of their first) posts to link to some or all of the studies which they wish to share with others. Then each author can update that post upon completion of any further studies. This would allow readers to access the maximum amount of specific studies in the shortest time and with the least amount of effort. Also, I was asked to start this thread, at least in part as a matter of circumstance, and am not necessarily assuming the responsibility of updating one central post containing the combined works of various authors.
This is a study of a fixed group of higher scoring players from 1946 to ~2007, and how they performed from season to season. It needs some improving, including more complete data, especially since the lockout, but overall I believe the methodology and results hold a lot of promise:
Improving Adjusted Scoring and Comparing Scoring of Top Tier Players Across Eras
The results may be used to A) assist in comparing offensive production across different seasons and eras, and B) see how "simple" adjusted goal/point data tends to help/hurt various seasons and eras.
This is sort of a subsequent, companion study, but totally separate methodology. It uses linear regression to study some factors which seem to most affect how the very top group of players' scoring fluctuates:
Using Regression to Adjust "Adjusted Points" for Top Tier Players 1968-Present
Adjusted Playoff Scoring
Best "Half Seasons" Since 1994
An Estimate of How the Available Hockey Population Pool Has Changed Over Time (Focuses on Goalies and Top Line Scorers)
Here are a few statistical pieces I've posted in the past in the history section.
Historical adjusted plus-minus
With or without you: Mario Lemieux
Historical special teams usage
Forwards playing the point on the power play
Historical strength of opposition for goaltenders
Best penalty killing defencemen post-expansion
Best power play defencemen post-expansion
Sakic vs Forsberg (even strength)
The Triple Crown Line
Home/road plus-minus splits
Analysis of Award Voting
"Applied" case studies
Counterpoint to Henri Richard Case Study
see post #241
seventieslord's "The Big Defensemen Study"
This is seventieslord's "The Big Defensemen Study"
Some of the goalie metrics that I'd published here a few years back (this link is to the 2008-09, and that thread has links back further):
This will all be on the goaltender site by the end of the summer (it's in the database, now I just need to get the database on the site - more tedious than it may sound).
C1958: I think Geocities no longer exists. In late August I'll upload all of the PDF files to another site.
I'll take a look at your Henri Richard post then as well. I will say that I have a much more favourable opinion of him now than I did several years ago (when the argument in his favour was essentially "he won a lot of Stanley Cups"). His defensive abilities are much better documented now, and his offense (once his relatively low PP ice time is taken into account) is impressive for the era.
Yurog: correct me if I've misunderstood, but are you trying to predict the results of Vezina voting based on goalie stats? That sounds very interesting; look forward to seeing the results. I once tried to do the same with Norris trophy voting but had no luck (presumably because defense is not really captured by any mainstream statistic, but obviously influences Norris voting).
I've moved a lot of the "whole threads" over to this forum, since they'll get more visibility here in a (currently) smaller forum than being buried a few years old in the other fora.
At some point, I may cull out single posts from larger threads and create new root threads here - if you have ideas for which posts deserve that treatment, please let me know.
Here's an extension I've published based on a paper I published in Informs-Interfaces which I can't post here:
Not sure if this thread is reserved for people who want to present their own research but I posted various links over the years. Thought I'd share in case people missed them.
Strategies for Pulling the Goalie in Hockey
David Beaudoin and Tim B. Swartz
NHL Draft Order Based on Mathematical
Adam M. Gold
The NHL determines draft order from a lottery that favors teams that are lowest in the standings.
Losing can help a franchise acquire a coveted prospect, which encourages fans to cheer
against their favorite teams. Draft order based on mathematical elimination would force the teams
that performed poorest into a highly competitive atmosphere. The teams that are eliminated earliest
would instead have more games to earn the top picks. If substandard teams are to survive in
mediocre markets, the injustice of incentives for losing must be eradicated.
The National Hockey League (NHL) formula that considers the reverse stand-
ings to determine draft order triggers logical reasoning that can destroy emo-
tional attachments and fanaticism, without which hockey teams cannot thrive.
Losing can help a franchise acquire a higher draft pick, which encourages fans
to cheer against their favorite team. Franchises that endure poor seasonal
performance should not accept considerable rejection and departure from sup-
porters. Although the teams with the most losses receive the highest draft
picks, the promise of future success by losing in the present creates a false
sense of security. This current formula yields the distressing paradox where
success and failure become synonymous. The NHL should use my formula to
create competitive draft orders and inspire fans with passion and optimism.
Referee Analytics: An Analysis of Penalty Rates by National Hockey League Officials
A Closer Look at the Relative Age Effect in the National Hockey League
A Closer Look at the Relative Age Effect in the National Hockey League
At young ages, a few extra months of development can make a big difference in size,
strength, and athletic ability. A child who turns 5 years old in January will be nearly 20% older by
the time a child born in December has their 5th birthday. In many sports, including hockey,
children born in the early months of the calendar year get noticed by their coaches because of the
superiority they demonstrate due to their age advantage. As a result, boys born early in the year
are more likely to reach the professional ranks of the National Hockey League (NHL). The
phenomenon just described has been labeled the relative age effect (RAE). Previous work studying
the RAE in the NHL has focused on individual NHL seasons, often encompassing many of the
same players across multiple seasons. We investigate the RAE using complete data on every
player who has ever played in the NHL. We focus the majority of our analysis on Canadian born
players and examine the RAE across hockey position and hall-of-fame status. For the first time,
we provide strong evidence of when the RAE began to manifest itself in Canada. Our change point
analysis indicates that the RAE began for players born since 1951. Finally, we make a case for
what initiated this change in the way young hockey players develop, particularly in Canada, which
produced over 90% of NHL players at that time.
I recently looked at the possibility of using a player's change in performance in his CHL playoffs to predict his change in performance come NHL playoff time.
Take a read at this article, it pertains to playoff "clutchness"
Here's a link to the VsX study we worked up mostly in the ATD section.
Measuring Teams’ Draft Success Using Analytics:
And a part 2, breaking down the draft, position by position:
Greatest goal scorers relative to the average first-liner in the season in which they scored a lot of goals. By "a lot", I mean, primarily, one of the top three placings for a given regular season.
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