This week, Garret and Rhys welcome internet friend and Flames fan Mike Fail (@MikeFAIL) to the podcast to discuss the Jets recent trade, the Canucks outlook at the deadline, Mike’s love of John Scott, and how great Jaromir Jagr has been through his career. We also react in real time to the David Clarkson news! Join us after the jump to listen!
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Hey everyone.
A bit of a change of pace for Hockey-Graphs, here is a bit of an informal blog post. There are two separate things I want to address.
First thing:
I made a mistake.
Long ago on an article about Corsi and context, I made an error with moving the data from one spreadsheet into another. Everything in the specific article was actually correct. However, I had linked to a summarized data table on Google docs though that had some erroneous data on it.
The Google doc had summarized the average goal differentials for sets of players given their position in the depth charts and their Corsi%. What had happened is I accidentally copied 2nd line and 3rd line forwards in both their appropriate place and where 2nd and 3rd pair defenders should go. The online document has since been corrected and can be viewed here.
I made another mistake though in building an article off of that Google document. This article used the previous data in creating a quick model to estimate the goal impact difference between two players with differing Corsi percentages. The image has since been corrected.
I want to always be clear of my methods and my intentions, so this is why I wanted to post this to you.
Second thing:
Far smaller detail, the Hockey-Graphs podcast will be postponed until probably Friday. Rhys and I were not able to find a time convenient to both of us in order to record a session until then.
Sorry.
Until next time and thank you for reading and supporting our work.
There has been a few tries in trying to find what drives special team success on the penalty kill and the power play. One thing though that hasn’t been talked about enough is the time factor and how it can impact a team.
Image by Erich Schutt, via Wikimedia Commons
As any person interested in hockey stats should do, I’ve been gradually building my own personal database of player information that I can use when Y3K robs my future post-human self of cloud data for 3 seconds. To that end, player size wasn’t a huge priority but I knew eventually I’d want to have it, if only to think about how normal-sized I’d be in the 1920s NHL. In the process of bringing in all that data, I decided to do a little demographic work on player height and weight. We all know the players are bigger now than they were before, but by how much? And is there greater variance in size now or in the past?
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Welcome to the fifth episode of the Hockey Graphs podcast, where Rhys Jessop (of Canucks Army and That’s Offside) and Garret Hohl (of Jets Nation and Hockey-Graphs) continue talking about hockey while learning how to podcast. Join us as we talk about Chris Tanev negotiations, RFA statuses and the cap, Olli Jokinen trade, the trade deadline and what it means to a few teams. Continue reading
Welcome to the fifth episode of the Hockey Graphs podcast, where Rhys Jessop (of Canucks Army and That’s Offside) and Garret Hohl (of Jets Nation and Hockey-Graphs) continue talking about hockey while learning how to podcast. Join us as we talk about fixing the Oilers and Leafs in one swoop, the Canucks BIG pick-up, and the Sabres-Jets trade. Continue reading
Last time we looked at the relationship between hit and goal differentials. We showed that the outhit team tends to also be the outscoring team.
On Twitter, the subject of playoffs naturally came up. Do physical teams get an edge in the post-season?
I’ve been already pulling some data on the playoffs and doing some studies. I thought this would be a good opportunity to show a few of my early findings.
From Wikimedia Commons
The hit statistic rivals the faceoff in praise by some more traditional hockey analysts. Both statistics are also similarly over valued in terms of their impact to the game. There has been work previously shown that the hitting statistic actually has a negative relationship with winning.
I wanted to look into this just a little bit further. I went to War-On-Ice and downloaded data for every NHL game since October 2007. I then cleaned the data and took a little look. Continue reading
Welcome to the fourth episode of the Hockey Graphs podcast, where Rhys Jessop (of Canucks Army and That’s Offside) and Garret Hohl continue talking about hockey while learning how to podcast. Join us as we talk about the Super Bowl, random correlations, Michael Hutchinson, save percentage, Zach Kassian, the Vancouver Canucks soon to become big trade, and other random thoughts. Continue reading
Last Year, I unveiled a hockey version of the baseball Marcels forecasting system in an attempt to forecast the future performance of goalies. The idea behind Marcels is simple: we take the last few years of a player’s performance and then weight more recent numbers higher than older numbers. In addition, we regress the player’s #s to the mean (with a player who has a larger sample being regressed less than one with a smaller sample) and, if we’re projecting for the future, we adjust the overall #s for aging. Again, this is a very very basic projecting system, but its’ been proven to be incredibly well founded for baseball, and probably for hockey as well.
So let’s take a look at how things have changed now that we have data from the most recent season. We now have a few goalies with enough data to run Marcels on that we didn’t previously (although barely in most cases) and a few goalies have had large turns in one way or another in their career, which changes the projections.
Again, as a reminder, here is our methodology:
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