What Happens When We Use Analytics Tracking on 8 Year Olds?

A recent video by USA Hockey brings together two of my current interests, hockey analytics and minor hockey.* One of the things coming from the analytics movement is the development of technology to better track the actual game play of NHL players. Recently we saw some of this technology with the 2015 NHL All Star game which incorporated computer chips in the jerseys of the players. This type of technology has been generating a lot of attention as it may improve and change our understanding of hockey performance (see my February 18th blog for more on this).

While this sort of technology applied to the NHL seems really cool, the use of this technology to better understand the game for young kids and how to provide an environment that maximizes their development and interest in the sport could provide important insights. That’s where this recent video comes in. USA Hockey took a group of kids from Detroit’s Little Caesars 8U team and used microchip (RFID ) technology to track the kids in full-ice as well as half-ice and cross-ice game play. They measured things like how often they possess the puck, number of shots, pass attempts, etc and looked at how these changed across different ice sizes.

The findings show how much kids benefit from the smaller ice-surface play. This result probably isn’t that surprising, as I know many who have argued for smaller ice surfaces for young kids anecdotally, but this video provides data which supports this. For skill development, this is great to know, and for keeping kids interested in the game and not getting turned off at an early age, this also proves important.

In Winnipeg, games at 5 and 6 years old are full ice games. I’ve had two kids go through this and I’ve experienced it with a kid who skated through everyone scoring 5 or 6 goals a game (and so possessed the puck for most of the game), and I’ve experienced it with a kid that never got to touch the puck and would quickly become frustrated or lose interest during the game. Both kids have always really enjoyed 3 on 3 at a place in Winnipeg known as The Rink. This is partly due to the unstructured nature of 3 on 3, but also due to the fact that The Rink ice surface is much smaller than a full ice surface. The kids therefore get many more touches with the puck, and are always engaged in puck battles and pressure due to the small quarters, in line with the points raised in the video.

My understanding is that Hockey Manitoba is moving towards games using less than full ice for 5 and 6 year old kids, and I look forward to seeing how my third son experiences the game this way when he starts.

If you have a few minutes, definitely give the video a watch.
*Thanks to Glenn Yates and Randy Aitken for both bringing this video to my attention!


Learning Hockey Analytics the Hard Way

Over the past year I’ve increasingly been hearing words such as Corsi, Fenwick, PDO, and Zone Starts when assessing NHL player performance. As someone interested in hockey as well as being a professor of sports economics I increasingly thought I should take the time to learn what these things are all about.

As many of you know, wanting to learn something, and finding the time to do it, can be two different things. I started teaching a class in sports economics a few years back as a way to get myself to finally learn about this area of the economics literature, and so I figured if I put a few classes of hockey analytics on my sports economics syllabus, then I’d have to teach it (and hence learn it) or else risk embarrassment when I didn’t deliver.

This isn’t a blog about responding to incentives though, it’s about highlighting a few of the interesting things I came across in my reading. First thing is that there are a lot of sites available with data for these different hockey metrics. These sites are a great way to learn what the main measures are that people are using, and they usually contain a description of the measures somewhere on the site. Sites such as Behind the Net, Progressive Hockey, and Hockey Analysis are great places to start. As well, the NHL on its NHL.COM website will be adding a range of hockey analytics data (around 30 different measures) soon, and so is something to keep an eye on as well.

In terms of readings for hockey analytics, I didn’t rely on academic articles so much as what the hockey press and related bloggers have written in this area. Benjamin Wendorf at the Hockey News has a short but informative introduction to hockey analytics, as does Sean McIndoe and Steve Burtch . Coming from these articles you get a sense of what measures people use, how they have changed the way fans and team officials view player and team performance, and give a sense of the things to come in hockey analytics.

The Burtch article is especially interesting as it spends some time discussing the psychology of how humans make decisions, and how mental short cuts and small sample sizes can all lead to poorly made judgements and decisions, leading the reader to better understand how the new approach to hockey analytics can help partially overcome some of these problems.

Something mentioned in McIndoe’s article and seen recently with the NHL All-Star Game is the use of microchip technology in the sweaters of players as well as puck to provide real time data on things like player speed, how fast the puck is shot, possession time, or whether the player enters the zone with possession. As well through the reliance on microchips, we should see increased standardization of the data itself. For more, Alex Prewitt of the Washington Post has a great article on what microchip technology might mean for player tracking.

I’m still a bit of a beginner with these things but I will be teaching a 3 week course on sports economics in May and so will be sure to update this blog with what’s new at the time in this evolving area of hockey assessment.