The NHLE Calculator

Convenience is everything nowadays.  

We want everything to be as centralized as possible – with
apps, news, etc all in one place – and everything done for us to the largest
possible extent. To that end, I’ve taken the initiative to simplify and
centralize the very common calculation of a hockey player’s NHLE, by creating a
calculator for it. To my knowledge, it’s the first of its kind that is publicly
available (this determined by one Google search and quick scan of the results),
but I could be wrong.

For those who are unaware of what NHLE is, you can read up on the topic from the creator himself, Gabriel Desjardins.

NHLE has been evolved and groomed by another hockey
analytics pioneer, Rob Vollman, since Desjardins’ introduction of it and I’ve
used Vollman’s latest NHLE equivalencies in the design of the calculator.
Unfortunately, the calculations are hard coded into the program so if/when these
equivalencies change, I will have to manually update it.

You can download the NHLE Calculator from my Dropbox page here, and store it wherever your heart desires for future use.

It has 37 leagues integrated and turns the previously tedious process into a three step,
tic-tac-toe play.

No more scouring the Internet for equivalencies and then whipping
out an actual calculator for manual calculations. 

It has gone through a few rounds of testing but there will still probably be bugs here and there. If you find any more, you can email me at croatis@futureconsiderations.ca and I’ll get them straightened out. If there’s an appetite for it, there’s the potential to imbed it on a website and have it be an online tool. 

Once more, here’s the link to download the NHLE Calculator.

Hope you all enjoy it. 

  • beloch

    Here are the NHLE conversion factors the calculator uses:

    • QMJHL 0.26
    • AHL 0.47
    • WHL 0.27
    • WCHA 0.44
    • NCHC 0.41
    • NLA 0.4
    • ECAC 0.23
    • Big-10 0.35
    • CCHA 0.32
    • H-East 0.37
    • NHL 1.0
    • MHL 0.18
    • OHL 0.32
    • ECHL 0.22
    • SHL 0.6
    • SMLIIGA 0.29
    • KHL 0.8
    • VHL 0.38
    • SEL 0.6
    • USHL 0.27
    • Allsvenskan 0.8
    • SuperElit 0.2
    • BCHL 0.13
    • DEL 0.52
    • CZECH 0.52
    • JrLiiga 0.36
    • CZECH2 0.29
    • AJHL 0.15
    • CCHL 0.15
    • High School 0.08
    • 2.Gbun 0.16
    • J18 Allsvenskan 0.16
    • J18 Elit 0.16
    • u20 0.55
    • Austria 0.08
    • CHL 0.3
    • U19 0.3

    For anyone not familiar with NHLE, the formula is dead simple:

    NHLE = Points / Number of Games * NHLE Conversion Factor for League (from above list) * 82

  • Gary Empey

    I have downloaded it and will unpack it after the game.

    This type of tool has the potential to be extremely useful.

    Like all analytical programs, a lot of hard work, on many different levels, goes into the creation and constant fine tuning to make it relevant.

    I thank you for your generosity in posting it here for us.

    I expect to make immediate use of it to show Justin where he went wrong.

  • Spoils

    I don’t think the NHLE necessarily measures league difficulty, it only measures what prospects are expected to score in the NHL the following year. This is influenced by the prospect’s age, their projected role and possibly a difference in the league’s roster size in the case of the ECHL. Therefore the score of 0.8 for Allsvenskan and 0.6 for the SHL could possibly be accurate.

    It might mean that the average age for the player from Allsvenskan is between 18-19 and perhaps the average SHL rookie in the NHL/AHL is in their early 20s. If the figure has little predictive power it might be an artifact from a small sample size.

    NHLE overestimates the difficulty of the junior leagues. The NHLE for the AHL for its few 18-19 year olds is around 0.65 and not 0.47. So it might be better to use the 0.65 when comparing Oliver Kylington to Rasmus Andersson for example.

  • Christian, I believe I know what caused the confusion with some of those factors.

    As you mentioned, your factors are based on the spreadsheet I provided, which includes all the data for any player who went to the NHL from virtually any league whatsoever, right?

    And, it also includes the formula for calculating translation factors for yourself. Did you apply that formula to every league in the spreadsheet?

    If so, the problem is that there’s not enough data for the vast majority of those leagues – that’s why I don’t publish them, and why they’re not included in that first page. I bet that David Pastrnak alone caused the odd result with the Allsvenskan.

    If you absolutely must have a translation factor for a league that rarely sends players directly to the NHL, consider using the Wilson Method of calculating it through an intermediary league, like the AHL or the SHL.

    I also recommend flipping through the chapter on translation factors in the first Hockey Abstract (the blue book). It has a far more detail and background on how to use and calculate translation factors than I can include here.