Grading each NHL team's draft performance

rubenflamshep

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Dec 6, 2023
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I've created a tool that, building on a some previous work (see Acknowledgements below), allows us to score each NHL team's draft performance.

Basically, for each NHL draft pick 1 through 200ish we can look at the average number of NHL games played by each pick. Schuckers notices that there's high variability in the average number of NHL games played by later picks:
Screenshot 2024-06-08 at 3.36.13 PM.png

We can smooth this by taking a rolling average for each pick that includes the 4 picks before and after:
1717879345741.png


This gives us an "expected games played curve" (eGP curve); the number of games you would expect a draft pick to play over their entire NHL career¹.

We can take this one step further by breaking out the eGP curve into separate years post-draft. So you'd have a separate curve for Y1 post draft, Y2, etc. They would look something like this:
Screenshot 2024-06-08 at 5.03.47 PM.png


Now we have this set of eGP curves and each draft pick's actual number of games played each year post draft. Subtracting the actual GP against the expected GP for each year gives us a score for that pick. We sum up those scores for every pick a team makes and we can score each team's draft performance across different periods of time!

To that end, scoring each team's draft over the last ten years, including 7 years post-draft for each pick reveals the following:
A chart showing NHL draft scored per team for the last ten years. Carolina, leave some draft picks for the rest of us.


The time period and number of post-draft years to include are both customizable. You can also click into a team to reveal the picks that make up their score as well as an individual pick to see how that pick developed:
Screenshot 2024-06-08 at 4.08.27 PM.png


There are some obvious limitations:
  • It doesn't account for injure/death so the Leafs get heavily penalized for their pick of Rodion Amirov who unfortunately died of brain cancer (maybe have a list of null players that don't get scored?)
  • This doesn't account for "star power" to a degree. The Avalanche get penalized for Cale Makar who look an extra year to develop (maybe use avg point share instead of avg gp?).
I would love to hear from others! Is it useful? Confusing? Lmk your thoughts :)

¹There are some intricacies that should be acknowledged/discussed here (e.g., later picks are very bimodal; they likely either have a decent NHL career or 0 games) but I'm going to gloss over them for the sake of keeping the length of this post manageable.

Acknowledgements:

Schuckers' seminal work used a 200GP threshold and looked at the probability of each pick becoming an NHL player (using a 200GP threshold). Moreau builds on this using some very mathy functional data analysis. Nandakumar actually rates each NHL team's draft using a game-theory-based retrospective scoring system.
 

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Killswitch

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May 22, 2022
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Would this affect teams with fewer picks vs those rebuilding and have lots, especially since those picks likely are top picks vs later round? Teams trying to win generally make trades that cost 1st, 2nd, and 3rd, rather than 5, 6, or 7.
 

rubenflamshep

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Dec 6, 2023
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Would this affect teams with fewer picks vs those rebuilding and have lots, especially since those picks likely are top picks vs later round? Teams trying to win generally make trades that cost 1st, 2nd, and 3rd, rather than 5, 6, or 7.
Great question! So two points:
  1. Currently, there isn't a correction for number of picks. It's potentially in the cards but I haven't noticed anything that would compel me to add it. If you consistently pick well you'll be positive and vice versa, though the quantity of picks would affect the magnitude of how postive/negative you are. A cherry picked example from 2011, Tampa only has 4 picks and manages to hit on all of them while Toronto has 8 picks and only hits on Leivo:
    Screenshot 2024-06-30 at 4.07.47 PM.png
    Screenshot 2024-06-30 at 4.07.58 PM.png
  2. Each pick is normalized against the average number of NHL games that that pick has historically played. So it shouldn't matter if the picks are later or earlier. For example, from 2011, Florida basically breaks even on Huberbeau because even though he plays 272 games in the first five years post draft, the average fourth overall pick actually plays 289 games over that same timespan:
    Screenshot 2024-06-30 at 4.13.57 PM.png
 

STL fan in MN

Registered User
Aug 16, 2007
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This is fantastic work! Bravo and thank you.

  • This doesn't account for "star power" to a degree. The Avalanche get penalized for Cale Makar who look an extra year to develop (maybe use avg point share instead of avg gp?).
But yes, I’d agree games played likely isn’t the best measurement. Maybe something like wins above replacement vs expected wins above replacement? Or like you said, point share. Something that would show the value of what each player contributes more than simply being in the lineup (games played).
 
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rubenflamshep

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Dec 6, 2023
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scoutthe.xyz
This is fantastic work! Bravo and thank you.


But yes, I’d agree games played likely isn’t the best measurement. Maybe something like wins above replacement vs expected wins above replacement? Or like you said, point share. Something that would show the value of what each player contributes more than simply being in the lineup (games played).
Yup, will take a gander at those with an eye to implementing one!
The 4 picks range for later rounds may be a bit too small as well. Variance in later rounds is much greater than earlier ones. Players in the 6th round vs 7th round are generally rated nearly identically for example.
I take your point, taking the average this way results in a mostly smooth expected game curve (blue line below) but a longer pick range will smooth out the line even more. Split between that and just slapping a log regression on it (which is what we're trying to approach anyways by increasing the pick range)
Screenshot 2024-07-06 at 10.30.19 PM.png
 

GenoMeowkin

Registered User
Jul 8, 2024
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Great work! Have you considered splitting positions, as forwards at the same draft position tend to become NHLers sooner than D-men (looks like your data exclude goalies anyway)? Also for the curve, have you considered just fitting a power-law or logarithmic curve instead of taking averages?
 
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Bond

Registered User
May 10, 2012
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Any reason why Dallas shows so poorly on this system? Athletic has them as one of the best drafting teams.
 

SwedishFire

Registered User
Mar 3, 2011
5,435
1,906
Imterrsting to see that up to sel3ctipn 180, there is an ok number of being NHLers.
Wich means up to 6th round. 7th round is a dart throwing on a paper - game.
 

Drumman44

Kyle Beach Deserved Better
May 2, 2017
1,960
2,836
What did you use to put this together? Python? Can I ask you for some advice?
Going to guess it's an R Shiny app?

Also I kind of love this player comparison tool

1720623470163.png


1720623397354.png


Really shows how young Sid and Bedard were when they made the Big Show

1720623560014.png
 
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PenguinSuitedUp

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Oct 2, 2019
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This is really cool work and you have obviously put a lot of thought and energy into it. I just want to ask whether you’ve thought of using a separate metric than games played? For a team like the Blue Jackets, it’s going to be a lot easier for picks to break into the nhl and get games played. I’d be more curious about a metric that accounts for quality of those games played as well. There are already a lot of options out there, but something as simple as a cumulative WAR could be ripped from evolvinghockey and give you a better analysis.
 

coooldude

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Jul 25, 2007
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This is really cool work and you have obviously put a lot of thought and energy into it. I just want to ask whether you’ve thought of using a separate metric than games played? For a team like the Blue Jackets, it’s going to be a lot easier for picks to break into the nhl and get games played. I’d be more curious about a metric that accounts for quality of those games played as well. There are already a lot of options out there, but something as simple as a cumulative WAR could be ripped from evolvinghockey and give you a better analysis.
Having just gotten into a debate on the Sharks boards re: our drafting from 2003-2012 (not covered in this analysis) and seeing that a lot of our major GP wins were depth or role players, +1 to cumulative WAR, if such stats go back far enough. Otherwise, awesome work here!
 

Hockeyville USA

Registered User
Dec 30, 2023
3,863
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Any reason why Dallas shows so poorly on this system? Athletic has them as one of the best drafting teams.
Because Dallas was dogshit in 2013, 2014, most of 2015, 2016, 2018. Once this model skews towards more recent years, Dallas will jump up closer to the top. Nichushkin not figuring it out until later, Honka busting, Gurianov underwhelming, Tufte being a bum, and Dellandrea being quite mid won't help. Not to mention Elie, Desrosiers, Hansson, Pollock, Peters, Karlstrom, and Eriksson basically doing nothing.
 

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