# AN ARGUMENT FOR NHLE

June 24 2014 08:00AM

NHLe is an equivalency formula used by some in the hockey analytics community.  It’s a method of standardizing scoring across various major and junior leagues.  Standardized scoring gives an idea of how players, generally younger prospects, perform at the NHL level. Some argue its merit as a valuable metric in assessing future performance.  The following provides a framework of how it can be used as a possible drafting qualifier.

The method was developed by Gabe Desjardins a number of years ago.  You can also find some more information about NHLe over at Matchsticks & Gasoline, our Calgary Flames blogging comrades.

The equation looks like this …

[(Points ÷ Games Played) x 82] x League NHLe Value=NHLe

Here’s an example of how it works…

The translation for the KHL is 0.82, the translation for the NCAA is 0.41, the translation for the WHL is 0.3 and the translation for high school is roughly 0.07.  Let’s assume that four players scores at the same PPG in four separate leagues, let’s say 60 points in 50 games (PPG of 1.2).  The players' corresponding NHLe (when we scale it over 82 games) would be: KHL – 80.7; NCAA – 40.3; WHL – 29.5; HS – 6.9.  In summary, a soon to be drafted 18 year old player putting up those points in the KHL is a rock star generational-type prospect, a really good NCAA prospect, a decent WHL prospect and a very low probability high school prospect.

The knock on using NHLe as a method to project how a player is going to perform in the NHL is that it’s rarely completely accurate.  The equivalency is based on the average of how players have performed in the NHL the year after coming over and the standard deviation is huge (20-30%).  This is to say that most players don't score exactly where their NHLe suggests.

Where NHLe is beneficial, however, is as an indicator of future potential offensive scoring, in a general sense.  It’s not perfect but we will see in a minute why NHLe, and especially high NHLes, can be used to help predict future offense.

## THE NUMBERS

 Player NHLe Games PPG Draft Year Number Draft PPG Age at Draft Crosby, Sidney 66.7 550 1.4 2005 1 2.7 17.90 Kane, Patrick 61.5 515 1.0 2007 1 2.5 18.61 Gagner, Sam 54.8 481 0.6 2007 6 2.2 17.88 Tavares, John 51.3 350 0.9 2009 1 2.1 18.78 Brassard, Derick 49.2 403 0.6 2006 6 2 18.77 Watson, Austin 49.2 6 0.2 2010 18 2 18.46 Hall, Taylor 45.7 246 0.9 2010 1 1.9 18.62 Kessel, Phil 44 586 0.8 2006 5 1.3 18.74 Schroeder, Jordan 43.2 56 0.3 2009 22 1.3 18.75 Stamkos, Steve 42.3 410 1.0 2008 1 1.7 18.39 Little, Bryan 41.9 486 0.6 2006 12 1.7 18.63 Cherepanov, Alexei 41.5 0 0.0 2007 17 1 Seguin, Tyler 41.4 283 0.7 2010 2 1.7 18.41 Granlund, Mikael 41.2 90 0.5 2010 9 0.9 18.34 Kane, Evander 38.7 324 0.6 2009 4 2.2 17.86 Tarasenko, Vladimir 38.4 102 0.6 2010 16 0.6 18.55 Turris, Kyle 37.4 316 0.5 2007 3 2.2 17.87 Giroux, Claude 36.6 415 0.9 2006 22 1.5 18.46 Backstrom, Nicklas 36.1 495 1.0 2006 4 0.6 18.60 Voracek, Jakub 35.9 449 0.6 2007 7 1.5 17.87 Couture, Logan 35.5 297 0.7 2007 9 1.4 18.25 Ryan, Bobby 35.3 448 0.8 2005 2 1.4 18.29 Bailey, Joshua 35.2 406 0.4 2008 9 1.4 18.74 Skinner, Jeff 34.6 259 0.7 2010 7 1.4 18.12 Stewart, Chris 34.5 382 0.6 2006 18 1.4 18.67 Kadri, Nazem 34.3 177 0.6 2009 7 1.4 18.73 Van Riemsdyk, James 34.2 324 0.6 2007 2 2.1 18.15 Duchene, Matt 34.1 337 0.8 2009 3 1.4 18.45 Hamill, Zach 33.1 20 0.2 2007 8 1.4 18.76 Zagrapan, Marek 33.1 0 0.0 2005 13 1.4 18.56 Ennis, Tyler 32 267 0.6 2008 26 1.3 18.73 Wilson, Colin 31.8 291 0.5 2008 7 0.9 18.69 Bourret, Alex 31.5 0 0.0 2005 16 1.3 18.73 Esposito, Angelo 31.3 0 0.0 2007 20 1.3 18.35 Glennie, Scott 31.3 0 0.0 2009 8 1.3 18.35 Toews, Jonathan 31.2 484 0.9 2006 3 0.9 18.17 Schenn, Brayden 31 192 0.5 2009 5 1.3 17.85 Hodgson, Cody 30.8 211 0.6 2008 10 1.3 18.36 Brule, Gilbert 30.6 299 0.3 2005 6 1.2 18.49 Sheppard, James 30.3 323 0.2 2006 9 1.3 18.18 Downie, Steve 29.4 336 0.5 2005 29 1.2 18.24 Caron, Jordan 29.4 123 0.2 2009 25 1.2 18.66 Perron, David 29.2 418 0.6 2007 26 1.2 19.09 Connolly, Brett 29.2 84 0.2 2010 6 1.2 18.16 Boedker, Mikkel 29 338 0.4 2008 8 1.2 18.54 Boychuk, Zach 29 96 0.1 2008 14 1.2 18.74 Schwartz, Jaden 28.4 132 0.5 2010 14 1.4 18.01 Lewis, Trevor 27.5 276 0.2 2006 17 1.3 19.47 Mueller, Peter 27.4 297 0.5 2006 8 1.1 18.21 Hishon, Joey 27.3 0 0.0 2010 17 1.1 18.69 Foligno, Nick 26.5 466 0.4 2006 28 1.1 18.66 Eberle, Jordan 26.4 275 0.8 2008 22 1.1 18.13 McArdle, Kenndal 26 42 0.1 2005 20 1.1 18.48 Burmistrov, Alexander 25.8 194 0.3 2010 8 1 18.69 Kassian, Zack 25.4 156 0.3 2009 13 1 18.43 Staal, Jordan 24.6 561 0.6 2006 2 1 17.80 Bennett, Beau 24.6 47 0.4 2010 20 2.1 18.59 Howden, Quinton 24.6 34 0.2 2010 25 1 18.44 Beach, Kyle 24.6 0 0.0 2008 11 1 18.46 Leveille, Daultan 24.6 0 0.0 2008 29 1.8 17.89 Holland, Peter 24.2 68 0.3 2009 15 1 18.46 O'Marra, Ryan 24.2 33 0.2 2005 15 1 18.06 Nemis, Greg 24.2 15 0.1 2008 25 1 18.07 Johansen, Ryan 23.9 189 0.5 2010 4 1 17.91 Cogliano, Andrew 23.9 540 0.4 2005 25 2.1 18.04 Pouliot, Benoit 23.9 371 0.4 2005 4 1 18.75 Okposo, Kyle 23.8 390 0.6 2006 7 1.2 18.20 Setoguchi, Devin 22.8 459 0.5 2005 8 0.9 18.49 Niederreiter, Nino 22.7 145 0.3 2010 5 0.9 17.81 Etem, Emerson 22.2 67 0.3 2010 29 0.9 18.04 Skille, Jack 21.8 194 0.3 2005 7 1.1 18.12 Paajarvi, Magnus 21.7 218 0.3 2009 10 0.3 18.22 Pacioretty, Max 21.5 319 0.7 2007 22 1.1 18.61 Colborne, Joe 21.4 96 0.4 2008 16 1.6 18.41 Josefson, Jacob 20.5 118 0.2 2009 20 0.3 18.16 Leblanc, Louis 20.2 50 0.2 2009 18 1 18.42 Coyle, Charlie 19.7 107 0.4 2010 28 1.5 18.33 Sutter, Brandon 19.7 415 0.4 2007 11 0.8 18.37 MacMillan, Logan 19.2 0 0.0 2007 19 0.8 18.07 Tikhonov, Viktor 18.8 61 0.3 2008 28 0.3 20.13 Grabner, Michael 18.4 283 0.5 2006 14 0.7 18.73 Oshie, TJ 18.3 371 0.7 2005 24 3.2 18.52 Paradis, Philippe 18 0 0.0 2009 27 0.8 18.49 Ashton, Carter 17.6 47 0.1 2009 29 0.7 18.25 Nash, Riley 17.5 110 0.3 2007 21 1.6 18.14 Kuznetsov, Evgeny 17.2 17 0.5 2010 26 0.3 18.11 Nelson, Brock 16.8 72 0.4 2010 30 2.9 18.71 Filatov, Nikita 16.8 53 0.3 2008 6 0 18.10 Tedenby, Mattias 16.7 120 0.3 2008 24 0.3 18.35 Sheahan, Riley 15.4 44 0.5 2010 21 0.5 18.56 White, Patrick 15.4 0 0.0 2007 25 0.8 18.44 Palmieri, Kyle 14.9 141 0.4 2009 26 0.4 18.41 Johansson, Marcus 14 263 0.5 2009 24 0.2 18.73 Hayes, Kevin 13.7 0 0.0 2010 24 2.4 18.14 Bjugstad, Nick 13.2 87 0.4 2010 19 2.3 17.95 Kreider, Chris 12.4 89 0.4 2009 19 2.2 18.17 Berglund, Patrik 12.2 436 0.5 2006 25 0.2 18.07 Hanzal, Martin 11.8 456 0.5 2005 17 0.2 18.36 O'Brien, Jim 11.7 68 0.2 2007 29 0.3 18.41 Eller, Lars 11.6 286 0.4 2007 13 1.4 18.14 Gillies, Colton 11.4 154 0.1 2007 16 0.5 18.38 Frolik, Michael 11.1 430 0.4 2006 10 0.2 18.36 Tlusty, Jiri 10.8 344 0.4 2006 13 0.2 18.29 Backlund, Mikael 10.7 246 0.4 2007 24 0.2 18.12 Bergfors, Nicklas 2.6 173 0.5 2005 23 0 18.15 Kopitar, Anze 0 604 0.9 2005 11 0 17.85 Gustafsson, Anton 0 0 0.0 2008 21 0 18.34

This is a list of all the 1st round forward draft picks from 2005 to 2010.  The table is sorted by highest NHLe to lowest.  I’ve highlighted in blue all players that have scored at a rate of 0.6 (approximately 50 points per 82 games) to this point in their career.  This is not to say scoring below this is a bust.  There are many forwards that put up 30-40 points a year but are incredibly valuable for what else they do.  But the thought here is that in the 1st round a team’s main goal is to find an offensive threat.  The threshold for this was arbitrarily set at 0.6 PPG over their career.

Also, you'll notice some players that have barely had a chance to play in the bigs yet, as they may be finishing a college degree or playing out the end of a Euro contract.  They could very well come in and light it up when they get to the NHL.  Players with lower ppg could also increase their scoring dramatically over the coming years. This is just the data we have right now.

 NHLE PPG of 0.7+ PPG of 0.6+ PPG of 0.5+ 40+ 53.8% 76.9% 84.6% 30-39 28.0% 60.0% 72.0% 20-29 5.6% 13.9% 27.8% 0-19 6.5% 6.5% 29.0%

What we find from just looking at the data is that very rarely does a team end up with a player who averages less than 50 points a year (very early in their careers) if the prospect has an NHLe north of 35, this seems to be the “can’t miss” range.  Perhaps the player doesn’t end up being the best of the draft but putting up 50 points + year after year in the toughest league in the world is pretty good. If we dive a little bit deeper, looking at some predictive regression modeling, the story gets better.

Here’s a brief crash course on how regressions work ...

Regression is a statistical process for estimating the relationship among variables. The adjusted R2 gives an indication of what type of impact one variable or group of variables (i.e., the independent variables) is having on another variable or outcome (i.e., the dependent variable).  You want this as close to 1.0 as possible as it indicates a very strong relationship and a strong model. With regards to the independent variables being assessed in the model, you want a p-value as low as possible (e.g., anything lower than 0.1 is good in this case); that indicates the variable is a significant factor and plays a role in the dependent variable you’re looking at. In this case, the dependent variable is the player’s current NHL ppg.  The independent variables are draft year NHLe, position taken in the 1st round and draft year PPG.

NHLE: 1.90; P-Value: 0.06

Draft Number: -3.18; P-Value: 0.002

Draft Year PPG: 0.67; P-Value: 0.51

What we find is that this model explains about 24% of a player’s future PPG in the NHL.  It’s not the whole story but these simple three variables are explaining about a quarter of the story. In this model, NHLe and the draft position are helping to explain future performance in the NHL whereas draft year PPG is not in the least.  The higher a player’s NHLe and the higher they are chosen (often the highest NHLes go first … but not always) the higher their eventual PPG in the NHL should be. That's the main take-away.

Things like the player’s ability to drive possession, skating ability, compete level, attitude, willingness to learn, how they're developed after being drafted, QoT and QoC would likely make up the rest of this model. Those figures are much more difficult to track, especially at the junior/development level, however. One day we'll get there!

Back to this model. As you look back over drafts you'll often find players that end up “surprising” and far exceeding expectations based on where they were chosen (e.g., Giroux, P. Stastny, M. Savard, T. Fleury, Ribeiro, etc, etc, etc.) have the draft NHLe to suggest that they should be a very good player (35+).  They are skipped over for one reason or another (size, playing in an unknown overseas league, age, attitude, etc.) but surprises are more often than not players that should have gone higher if their NHLe was one of the main qualifiers for drafting.

To illustrate this point, if you reverse the process and look at the highest scorers in the NHL over the past 20 years you find that draft year NHLe still comes out as a significant predictor (R2: 0.16; p-value: 0.002) whereas the significance of draft position goes away. There’s enough late-round surprises in the data to tip the scale the other way.

## SUM IT UP

Regardless of how you slice it, junior/developmental league scoring is, in my mind, the single biggest predictor of future offensive performance. These numbers, just simple standardized counting principles, can be leveraged by NHL teams to draft better by taking a significant portion of the guessing out.  Maybe a team loses out on getting “the best player” here and there but if a team follows these principles they would likely draft a very, very good player again and again and again.

Start to factor in metrics like age (i.e., younger 35+ NHLes are better than older 35+ NHLes), massive NHLe jumps from their draft-1 year to their draft year (i.e., players that jump by 10-20 points) and individual primary, ev and total team point totals and the picture becomes clearer.  All this before ever even seeing a player play.

This year, there's five players (North American skaters anyways) that fit the "can't miss" 35+ NHLe mold in the draft class. They are: Sam Reinhart (43.1), Leon Draisaitl (40.4), Sam Bennett (39.3), Nikolaj Ehlers (39.3), Robert Fabbri (36.9). Dal Colle (34.9) is right there as well. Over-ager Louick Marcotte (35.5) also fits the bill but he's two years older than the rest of the crop.  He could be worth a late-round flier though. I bet we hear a lot about all of these guys in the coming years and they turn into very productive players for their respective teams.

Byron has always been curious about numbers and stats, especially related to hockey. His background includes schooling heavily-focused on psychology, economics and statistics and a professional background revolving around reseach, segmentation, data mining and statistics. His love for hockey is as deep as the ocean is wide. Tell him your questions and let him into your heart. Twitter: @Baderader; Email: byron.bader@gmail.com