Analytics and the Draft

Over the last few months, we’ve explored the history of analytics and how they should be applied to the game of hockey. Now that the season has ended for 23 of the league’s 31 teams, the draft is the next thing to look forward to for most fans in the league. In recent years, multiple outlets have examined the draft and attempted to boil evaluation down to various measures that correlate to an NHL career. I’m not the biggest fan of using the history of the draft to project future success as the game has changed immensely, as have what scouts look for in NHL talent. Gone are the days of low point, high PIM players going in the 1st round, or drafting with an emphasis on size. Nowadays, skill, speed, production and creativity (or as I like to call it, being good at hockey) are valued highly by nearly every team, especially in the 1st round.

The draft is a complicated beast, and just looking at a scoresheet doesn’t give you the full picture. Combining video/viewings with analytics is likely the strongest pathway forward, with studies now going so far as to examine keywords used in scouting reports to isolate players who may translate better to the NHL. Anyone who tells you one is the only option or is more valuable than the other is simply wrong. I may not be able to get around to 200 games a year, but I do have well over 20,000 games worth of production tracked across multiple leagues on multiple continents, all without needed to pay for travel. A competent NHL team can likely expect one or two of their seven draft picks to crack the NHL full time one day. If my tracking and analysis can increase that to two per draft, or five every two drafts, is that worthy of investment?

That leads me to the reason you’re here: The tracking document. Below is the link to the Google Sheet of 450 draft eligibles I’ve had my eye on. There is a glossary of terms within, but I’ll go through some of the basics below, as well as some notables.

https://docs.google.com/spreadsheets/d/10WL8y4MRedOtyR2p_s1ViJK2woJn2hz9liTQNymFwgc/edit?usp=sharing

I will note that this document will only be viewable, and will remain sorted by average ranking across 12 separate scouting services up to ~100th overall. The remainder are sorted by my patent-pending NHLe Score. These rankings will be updated as the draft approaches, and if anyone spots any discrepancies, please let me know at [email protected]. Any questions are open season as well, be they here or on Twitter @scouching.

One final note. For European leagues and non-CHL/USHL hockey, most metrics are all situations, or an estimation of even strength. There is no even strength shot data for the USHL or WHL as well, so dangerous shot metrics from those leagues are absent.

Below are a selection of metrics as well as some standouts:

• AgeAdg – Age, Position and League Adjusted NHLe Score
  • A score using league difficulty, a player’s INV% (explained below), age, and position to sum up a total evaluatory score. Above 30 is considered Top-Class
  • Standouts
    • Evan Bouchard
    • Ryan Merkley
    • Rasmus Dahlin
• GF%Rel – Goals For Percentage Relative to Teammates
  • The percentage of total goals scored while at even strength that are goals for, relative to the rest of the team.
  • Standouts
    • Johnny Gruden
    • Ty Smith
    • Nathan Dunkley
• GF% – Goals For Percentage
  • Percentage of total goals scored at even strength that are goals for
  • Standouts
    • Johnny Gruden
    • Andrei Svechnikov
    • Riley Sutter
• Inv% – Involvement Percentage
  • Defined as player points per game divided by team goals per game. Meant to remove a bit of team quality from evaluating raw production. 40% is considered top level in a given league.
  • Standouts
    • Bulat Shafigullin
    • Niklas Nordgren
    • Jonatan Berggren
• ESP1/60 – Even Strength Primary Points per Hour
  • Even strength goals and primary assists per 60 minutes of even strength ice time (non CHL/USHL is all situations)
  •  Standouts
    • Andrei Svechnikov
    • Joel Farabee
    • Oliver Wahlstrom
• ESP/60 – Even Strength Points per Hour
  • Even strength goals and assists per 60 minutes of even strength ice time (non CHL/USHL is all situations)
  • Standouts
    • Jake Wise
    • Joel Farabee
    • Jonny Gruden
• ES S/60 – Even Shots on Goal per Hour
  • Even strength shots on goal per 60 minutes of even strength ice time (non OHL/QMJHL/USHL is all situations)
  • Standouts
    • Oliver Wahlstrom
    • Filip Zadina
    • Michal Kvasnica
• ESP1Inv% – Even Strength Primary Point INV%
  • Defined as player even strength goals and primary assists per game divided by team even strength goals per game
  • Standouts
    • Andrei Svechnikov
    • Filip Zadina
    • Tyler Madden
• ESPInv% – Even Strength Point INV%
  • Defined as player even strength points per game divided by team even strength goals per game
  • Standouts
    • Filip Zadina
    • Andrei Svechnikov
    • Tyler Madden
• G% – Goal Involvement
  • Defined as a players goals per game divided by total team goals per game
  • Standouts
    • Bulat Shafigullin
    • Andrej Kukuca
    • Andrei Svechnikov
• P1 IPP – Even Strength Primary Points on Goals Scored on-ice Percentage
  • Percentage of even strength goals scored while on the ice where the player got a goal or primary assist.
  • Standouts
    • Jack Randl
    • Tristen Nielsen
    • Andrei Svechnikov
• IPP – Even Strength Points on Goals Scored on-ice Percentage
  • Percentage of even strength goals scored while on the ice where the player got a point
  • Standouts:
    • Jake Wise
    • Alexander Steeves
    • Jack Randl
• HD S% – High Danger Shot Percentage Share
  • Percentage of even strength shots coming from high danger areas
  • Standouts
    • Serron Noel
    • Curtis Douglas
    • Brady Hinz
• HDS/60 – High Danger Shots per Hour
  • Number of even strength shots coming from high danger areas per hour of ice time
  • Standings
    • Curtis Douglas
    • Serron Noel
    • Andrei Svechnikov
• H/MDS% – Even Strength High and Medium Danger Shot Percentage Share
  • Percentage of even strength shots coming from high and medium danger areas
  • Standouts
    • Serron Noel
    • Cam Hillis
    • Nathan Dunkley
• H/MDS/60 – Even Strength High and Medium Danger Shots per Hour
  • Number of even strength shots coming from high and medium danger areas per hour of ice time
  • Standouts
    • Andrei Svechnikov
    • Curtis Douglas
    • Serron Noel
• NHLxG – Even Strength Expected NHL Goals (applying shot danger to average NHL save percentages)
  • A very rough approximation of expected even strength goals based on danger of shots and average NHL save percentage.
  • Standouts
    • Andrei Svechnikov
    • Curtis Douglas
    • Filip Zadina
• Tot.Cat% – Total Catalyst Percentage (Sum of Offense and Defense, calculated separately)
  • A total percentage change in even strength goal differential relative to the team as a whole without the player
  • Standouts
    • Ty Smith
    • Jonny Gruden
    • Oliver Wahlstrom

Last thing is a thank you to everyone for reading this in advance and for taking the time to dive into some metrics. This is something I work towards in spare time continuously all year, and I’m happy to share it. Another huge thank you to Prospect-Stats.com and EliteProspects.com for being an invaluable tool to help monitor this, and any way I can support the sites, I’m happy to do so, and so should you. Last year’s sheet is located here, in case you would like to peruse that as well.

https://docs.google.com/spreadsheets/d/1LEi7A26DX5g8bKjqHez8RzPxjdp73UeSP8ozUsK-PBE/edit?usp=sharing

P.S: Being based in Toronto, using these metrics I’ve made a few changes to their recent draft picks, and here’s how I would’ve done things. Anyone missing would’ve been likely targets.

Follow Sir William Scouchington the III here –> @Scouching