How hot are advanced stats in the hockey world? Well, it’s been tough to fall in love with any particular website in the past two years because the folks running them keep getting hired by NHL franchises. It’s a good problem for the numbers community to have, I suppose.
But what about advanced stats for the prospect world? That’s another story altogether. One of the toughest aspects of forecasting and analyzing draft prospects is the fact that in most cases, you can’t even get time on ice numbers for players, even in major junior or the NCAA. Some websites have attempted to run Corsi numbers, but they are difficult to find on a consistent basis.
NHL teams are paying attention, however. Some run their own numbers, while others pay for the service. Bench Metrics, a company founded by USHL Sioux City coach Jay Varady and former CHL and USHL coach Michael Zucker, began with a coaching product several years ago. But for the past two years, the firm has been selling Scout Metrics, an advanced stats suite that gives teams a look at many different stat sorts for about 100 of the top prospects for the draft. Seeing as both Varady and Zucker come from coaching, it’s no surprise that they don’t see their product as a replacement for traditional scouting, but instead a tool to further the conversation on a player. And last year’s results were telling. Auston Matthews and Patrik Laine, for example, were very close together. And one player who has raised his profile and skated in NHL playoff games ranked particularly well: Charlie McAvoy, already looking like a steal for the Boston Bruins by going 14th overall in 2016.
“The data,” Zucker noted, “said he should have gone higher.”
Scout Metrics is still an evolving product and feedback from NHL clients is helping that process. Time on ice got the most buzz, while controlled zone entries and pass completion rates were requested by teams and implemented this year.
The company used an 11-game sample to draw its numbers. They started with eight, but found there was a little too much noise. The list of players is drawn off NHL Central Scouting’s list, but clients who buy VIP packages can even ask for certain players to be added to the roster (and get exclusive rights to those numbers).
Given how important the draft has become, it’s no surprise franchises are paying attention to advanced stats, even if the field is in its infancy.
“It’s a projection, just like anything in scouting,” said Arizona GM John Chayka, who comes from an advanced stats background himself. “These players are trending in certain directions and you have to take that into consideration, just like you have to take into consideration their skating when they are still evolving. There is certainly a little more variance in draft prospects, that’s why the hit rate is much lower than trading for a player or signing one in free agency. But it’s also the highest return on investment.”
There are a few more factors when it comes to prospects, however. In the NHL, you’re comparing apples to apples – but in the prospect ranks, the quality of competition can swing wildly. Teams have to keep in mind that a player blowing the hinges off a smaller Jr. A circuit may not have had the same success against men in Finland, for example.
“Just like the eye test, it’s difficult going league to league,” Chayka said. “It is a big consideration.”
There’s also the fact that some prospects are already NHL-sized, while others are lanky teens in need of years in the weight room. One scenario isn’t better than another, but both must be considered in evaluating a player’s ultimate upside, Chayka noted.
And of course, numbers alone aren’t going to be a death knell for any prospect; evaluation on many levels will always be necessary.
“We’re a data company,” Zucker said. “We’re careful not to project too much.”
But it is interesting to sift through that data. I got a sneak peek at some of Scout Metrics’ data and they have allowed me to share a bit here. The following represents the top five players in the 2017 draft class in three different categories (all numbers are from even-strength scenarios over an 11-game sample):
Net Shot Attempts
Controlled Zone Exits
Cale Makar, D, Brooks (AJHL): 106
Conor Timmins, D, Sault Ste. Marie (OHL): 72
Ian Mitchell, D, Spruce Grove (AJHL): 58
Josh Brook, D, Moose Jaw (WHL): 58
Juuso Valimaki, D, Tri-City (WHL): 58
Antoine Crete-Belzile, D, Blainville-Boisbriand (QMJHL): 92.4 percent
Jarret Tyszka, D, Seattle (WHL) : 91.3
Josh Brook, D, Moose Jaw (WHL): 90.2
Clayton Phillips, D, Fargo (USHL): 90.2
Ian Mitchell, D, Spruce Grove (AJHL): 89.7