News Article: The development of faceoff skills

CodyTheHuman

Registered User
Dec 31, 2014
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This is a good article. I enjoy what you write.

One issue though:
The only two players who fitted this trend were Kyle Brodziak and Marc Chouinard, who both seemingly got gradually worse on the dot as they got older and more experienced.

Fitted should just be fit.
 

cheesesteakarmor

Registered User
Jul 18, 2009
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Love it as always, Alex.

One suggestion and one question.

Suggestion: Don't use significant (you know better, stats man!). Use substantial. Also, what was the cut off for the number of faceoffs?

Question: In mapping the trends, did you identify anyone who has a more prominent slope? In other words, who became a better faceoff centerman faster? Alternatively, who has had a slower decline?

Much obliged.
 

Ryker

Registered User
Oct 3, 2008
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Hey Apples, I was just curious, but how much time on average would you say you spend on writing an article (including background research, not just the act of writing it up)?
 

Appleyard

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Mar 5, 2010
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Love it as always, Alex.

One suggestion and one question.

Suggestion: Don't use significant (you know better, stats man!). Use substantial. Also, what was the cut off for the number of faceoffs?

Question: In mapping the trends, did you identify anyone who has a more prominent slope? In other words, who became a better faceoff centerman faster? Alternatively, who has had a slower decline?

Much obliged.

Yeh, you are right, substantial would have been more apt!

The cut off was the hardest part. I decided on 5 per game, as when the faceoffs per game are averaged this is about the most guys predominately playing wing ever have... Benn, Steen and Brouwer were pretty much the only 'wingers' over 5 per game last season... but none maintained that over career, and none predominantly centers, so none included in the sample. I would have preferred higher... but when I started I felt it could be unworkable as so few players come into the league taking a large number of draws, and many players play parts of seasons at wing... the sample would have been far smaller and simply a list of elite faceoff guys with high scoring centers as well. (and I wanted to try an include guys who were not so good on the dot) One or two guys seasons were listed though with say ~4.8-4.9 per game... (not perfect I know.) SPSS seemed to be ok with the diagnostics at that point... any lower and it started shouting at me!

Though if I were submitting it for a University assignment I must admit I would feel slightly uncomfortable with some of the individual player stats (one or two of the guys towards the lower end of faceoffs taken who had years while injured and missing half of the games, their yearly stats looked fine and all fitted with what the model would predict (within standard deviation etc)... but after I finished I thought if I were to do it again I would probably knock it down to ~60 or so players and increase the threshold.)... though happy and confident to a high level with the overall year to year stats.

As for the 2nd question... I shall get back to that tomorrow! My laptop I did the work on is in a different city!

Hey Apples, I was just curious, but how much time on average would you say you spend on writing an article (including background research, not just the act of writing it up)?

It depends. This one and the last one on defensemen and their maturation the statistics were kind of semi-long term hobbies. (which annoys me everytime... as by the time they are finished I have thought of numerous ways to make them better. My 'draft pick value' stuff I posted here a few years ago was the worst for that... by the time I was half way through I wanted to start over, but it had taken weeks of a few hours a night a few times a week compiling the data, so I kind of stuck with something that I knew could be better. That study is something I am certainly going to re-do when I have more free time... hopefully this summer.) Just did bits on them for a few months before I really thought of putting them into article form, just to satisfy my own curiosity. As for the writing part, usually one evening... I am the kind of person (even with Academic work) who cannot put something down and go away from it, come back and continue easily... so for example the Lindblom article was written up in a big ~3 hour long session... but I knew what I wanted to write before I started. (the Couturier and Mason ones were similar I suppose, though took slightly less time to write up.)
 
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cheesesteakarmor

Registered User
Jul 18, 2009
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Yeh, you are right, substantial would have been more apt!

The cut off was the hardest part. I decided on 5 per game, as when the faceoffs per game are averaged this is about the most guys predominately playing wing ever have... Benn, Steen and Brouwer were pretty much the only 'wingers' over 5 per game last season... but none maintained that over career, and none predominantly centers, so none included in the sample. I would have preferred higher... but when I started I felt it could be unworkable as so few players come into the league taking a large number of draws, and many players play parts of seasons at wing... the sample would have been far smaller and simply a list of elite faceoff guys with high scoring centers as well. (and I wanted to try an include guys who were not so good on the dot) One or two guys seasons were listed though with say ~4.8-4.9 per game... (not perfect I know.) SPSS seemed to be ok with the diagnostics at that point... any lower and it started shouting at me!

Though if I were submitting it for a University assignment I must admit I would feel slightly uncomfortable with some of the individual player stats (one or two of the guys towards the lower end of faceoffs taken who had years while injured and missing half of the games, their yearly stats looked fine and all fitted with what the model would predict (within standard deviation etc)... but after I finished I thought if I were to do it again I would probably knock it down to ~60 or so players and increase the threshold.)... though happy and confident to a high level with the overall year to year stats.

As for the 2nd question... I shall get back to that tomorrow! My laptop I did the work on is in a different city!

Smooth using different time intervals. 1.5-2 year time intervals will help smooth out those anomalies. Stinks we have to work in such short time frames, otherwise I would recommend 3 and 5 year increments :)

Excited to see accelerating, persisting, and declining slopes. Very cool work amigo.
 

klutch

PP1 Specialist and Fat Slob
Dec 5, 2014
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Nice read and article Apple, I really enjoy your work. Keep up the good stuff man !
 

Appleyard

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Mar 5, 2010
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I will interpret fastest improvers as guys who improved and then maintained a similar production, not just fluke good years, both from start of career and during:

From start of career:

Joe Thornton: 43.3% to 48.7% from year 1 to 2. Improved ever since.

Matt Duchene: 44% to 50.4% from year 1 to 2. Improved pretty much ever since.

Travis Zajac: 46.9% to 51.2% from year 1 to 2. Improved ever since.

Chris Drury: 46.9% to 53.1% from year 1 to 2. Was a ~55% guy after that.

Patrice Bergeron: 49.4% to 54.7% from year 1 to 2. Got better since.

Joe Pavelski: 48.6% to 53.5% from year 1 to 2. Got better since.

Samuel Pahlsson: 44% to 49.8% from year 1 to 2. Kept improving after.

Jordan Staal: 37.1% to 47% from year 1 to 3. Improved almost every year since.

Boyd Gordon: 43% to 52.1% from year 1 to 3. Kept improving since.

Jason Spezza: 45.8% to 52.6% from year 1 to 3. Been at an average of ~54% since.

Clarke Wilm: 40.9% to 51.9% from year 1 to 3. Stayed ~that for rest of career.

Lars Eller: 42.4% to 49.3% from year 1 to 3. Improved ever since.

Between seasons:

Ryan Kesler: 46.1% to 53% between years 3 and 4. Has been great ever since.

Jeff Carter: Went from a consistent 48% guy to a consistent 53% guys between 4th and 5th season.

Anze Kopitar: Went from a consistent ~49.5% guy to a 53.5% guy between 5th and 6th season.

Some outliers:

Manny Malhotra: Was a 44% guy consistently for first 4 seasons. Between 4 and 6 jumped to a 54% guy, and kept improving since. He really stands out when all the players are plotted on a line chart... not just because he is kind of in his own up above 60% on more than two occasions.

Patrick Marleau: Between 8th and 9th year of career went from being a poor faceoff year in his first 8 seasons to a +50% guy almost ever since.

Eric Staal: Was around a ~44% guy until 7th season, where jumped to 48%... 8th season jumped to 52%... been around that ever since.

David Backes: Was a ~46% guy until 6th season. Jumped to 48%, then in 8th to 52%, where he has ~been since.

Declines:

Brodziak & Chouinard are really the only guys who got obviously worse continually.

Briere & Gomez seem to be in their own little group as guys who improved, peaked and then dropped back off. Almost every one else either maintains a similar % or keeps seeing marginal improvement or marginal decline.
 

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