If you've ever thought that sports analytics could only be implemented in national leagues, where there is plenty of data made publicly, then it's time to think again. Miles Hoaken is a first year Queen's University student in the Commerce program, that is the creator and director of the analytics department for the Queen's Men's Hockey team. In Miles' first year alongside the coaching staff, the team was able to break the school's record of most wins in a season (19) and finish second in the OUA Eastern conference. I sat down with Miles to talk about how he uses analytics to help make the team even better, and for tips on how other students can start getting into hockey analytics.
Thanks for coming today and agreeing to do this interview. I’m sure many students who support the Queen’s Men’s Hockey Team aren’t aware that there is an analytics department for the team, let alone that it’s run by a Queen’s student. Tell us a bit about who you are and what you do.
My name’s Miles Hoaken and I’m from Toronto. I started getting into hockey analytics when I was 13 years old. Basically, the Leafs lost game 7, blowing a 4-1 lead (as I’m sure a lot of you are aware), which made me realize that there might be another layer that myself and Leafs management weren’t paying attention to, and since they’re my childhood team I tend to follow them more. I started a blog when I was 13 years old, writing down some ideas that I had that were based on some hockey analytics, but not a lot since I was only 13 and I didn’t have the math background at the time to understand what some of the stats were. In 2014, the summer of analytics, I saw tons of people getting hired and realized it was realistic for analysts to get hired based on the work they produced on their blogs or Twitter, so I decided to get further into analytics, started writing more on my blog, and then in Grade 12 I got an analytics position with my high school team. I did statistical consulting on their play, mainly analyzing zone entries but varied depending on what the coach wanted from me on that day. From there, I parlayed that into my role with Queen’s, which is essentially running all their analytics and statistical operations. I basically serve as a coach on their coaching staff, so I’m right there in the office helping make decisions, advising the coach on certain strategy items, giving presentations to the players on occasion, and running that whole operation. We take a variety of stats, mainly pertaining to offensive output since that was the area coach was most interested in.
So you’re 18 years old and working with the coaches for the Varsity Hockey Team here at Queen’s for players who are often 3-5 years older than you. Cool to think about. How do you get the data that you use?
I get all the data live at the games, and it’s all tracked by hand. I print-out templates before the game that have everything that I’m going to fill out, for example, for an entry chart I’ll have categories to see who entered the zone, what type of entry it was (controlled or uncontrolled), what general location it was, and then some counting stats. To get the shot locations, I simply mark them down on a piece of paper and fill in the numbers in my spreadsheet after the game. This works well for us since we are trying to do them all live. I unfortunately don’t have the time luxury to go through all the games for many different stats and many different viewings, because I would probably fail all my school courses if I did. So it has to all be live, and has to all be fast, so the best way to do that right now is by hand. Next year, we have five other people helping me track stats, which should allow us to have more data to work with, but the long-term goal is to automate these parts of the job so that when I graduate, the analytics department could be run by one person at the click of a button.
Are you looking for more students to help out?
Right now we’ve filled all of our data-tracker positions for the upcoming year. We’re always looking for coders who can help out on some of the stuff on the presentation side since building a portal for the coaches is something that I’m trying to do. At my current level of coding I don’t think I could do it, but eventually with some help I think that we can get there. Keep watching our Facebook page, after next-year we’ll be looking for more data-trackers.
How has the coaching staff responded to your work with them?
The whole staff has been very receptive to analytics. Sometimes I come in with crazy ideas, but they really bear with me and take into account what I’m saying. Credit goes to Brett Gibson, when I walked into his office in the first meeting, I was a bit of an unknown and we were going to use an iPad app to track stats. I was able to convince him that the iPad app wasn’t that good and would be a waste of his money and the program’s money and that they should instead trust me and my templates. Maybe it takes a little bit of logic and a bit of crazy to trust an 18 year-old that he had never met before, but he put his faith in me and gave me this role and I will forever be grateful to him for that. He’s done a great job of incorporating me into the decisions and making sure my voice is heard. It’s something he didn’t have to do but I’m really glad he did. It’s been a great situation with the coaches, and coach Gibson has brought the program from a point where we only had 4 former CHLers when he started, to 21 CHLers now so that speaks to his work ethic and commitment to the program for sure.
What’s your relationship like with the players? Do you think they’ve bought in to your recommendations?
I’ve presented to them once so far. It was interesting to read the room because it seemed like the people at the top of the list for the stats I was presenting had a quicker buy-in to what I was talking about. The players at the bottom of the list seemed to look a little bit more confused by it, but what I found that the players near the bottom of the list actually had a larger increase in these stats than those near the top of the list, which made me think they were responding well to it. They also get access to my reports after every game.
Do you do any coding as part of what you do?
I would say that half of my job is in the rink doing the tracking and recommendations, and the other half is during the week, coding and making programs. The report I give to the coach after every game contains some offensive statistics which are all generated by graphs on the program R. I set it up so that I can simply change the game number and it will generate the code for that game. It’s a big part of what I do, if anyone is looking to get into hockey analytics, I would say the first thing to learn is coding because it will just make everything a lot easier. I also use coding to generate statistics on the league. I have a web scraper that takes the raw data from the U-Sports website and then turns it into ‘fancy stats’ – Goals for %, Shots for %, some I’m even able to get for 5v5 play through the data that they give us. So coding is a big part of it, I use R, personally but there is a big debate in the hockey analytics community between R and Python – you really can’t go wrong with either. I’m learning Python as part of a coding course at Queen’s next year (CISC121), but R is what I started with and the one I feel the most comfortable with.
This year you spoke about what you do for the Queen's Men's Hockey Team at VANHAC (Vancouver Hockey Analytics Conference). The presentation link is here. Tell us about your experience at VANHAC. Would you recommend it for those who are interested in working or learning about hockey analytics?
VANHAC was a really great experience for me. I went as a high school student, it was sort of like my grad trip. Some people go on S-Trip, I went to a hockey analytics conference which I think tells you all you need to know about my personality and my passion for this. *laughs* VANHAC is really awesome, it’s probably the best conference in North America, in terms of your value and hockey analytics specifically. Sloan (MIT) is the big one for sports analytics in general which I hope to go to someday. Really though, if you want to meet people from NHL teams, see some of the best research that’s come out recently, you have to go to VANHAC. It’s great because you don’t necessarily need to be an expert to go, some people were there with no experience whatsoever, didn’t know what Corsi was and ended up really enjoying it so it’s a really fun environment. The hockey analytics community is one of the most welcoming communities ever. When I was presenting there this year I didn’t feel nervous at all, so I definitely recommend it to any hockey analytics fan or even someone just trying to get into it.
Do you think we’ll ever see analytics at the forefront of U-Sports hockey? I feel like if more students knew that what you do is possible, there might be more focus towards it leading to each team having their own student-led analytics department.
At VANHAC, Brad Mills (@MillsBradley11) who’s the COO of Hockey Data (@HockeyDataInc), he approached me after my presentation and since he played in the NHL, we started talking about how the game is changing from the advances of analytics since he played. He said that given the amount of teams in U-Sports, and given all the statistics I was using, it would cost ~$11,000 to do what I do for every single team in the regular season. I was surprised at how little it was, but at the same time, I mentioned “That $11,000 is only worth it if we have all the data and nobody else does” since that’s what gives us our competitive advantage. That was actually one of the questions I received after my presentations which was “Do you do any analysis on players from other teams” and the answer to that is no, because the public information I can get is points, and I have no idea where these points are coming from necessarily, or if their skilled in any other way that a micro-stat could capture but I don’t have access to it. There are definitely people like me at other Universities, maybe not to the same extent or scale since we’re becoming one of the more advanced ones, especially given the amount of trackers we’ll have next year. I know Western and UOttawa have an analytics person as well but some teams don’t even have that voice in the room, and with that sometimes you can get into groupthink.
You’re active on Twitter (@SmoakinHoaken). How has Twitter been a learning tool for you?
Twitter has been huge for me, I got Twitter when I was 13, which you can probably tell from my handle (@SmoakinHoaken) (Hannah Montana reference). It’s been really key, people post their research on Twitter first, and people have gotten hired not because of Twitter, but because of the work they’ve put out on Twitter. It’s great for questions too, if you’re new to hockey analytics, you can use the hashtag #HockeyHelper and Alex Novet or someone from @HockeyGraphs will reply to you really fast with some advice.
Aside from @QSAOqueens, what are 5 Twitter accounts that you recommend hockey analytics enthusiasts to follow?
@IneffectiveMath – Micah Blake McCurdy (www.hockeyviz.com) – I got to meet him at VANHAC and he posts a lot of cool visuals and has a patreon with premium content which allows him to make even more graphs. His theme is that numbers are tired, and pictures are wired, which I really like. We’re actually trying to incorporate more pictures and visuals with Queen’s next year.
@SteveBurtch – I think he said he tweets a thousand times a month or something like that, so you get a lot of content that’s interesting. As he’s joked about himself, he has a surprisingly low “Bad-takes/60 tweets”, so you should definitely follow him.
@nnstats - Superbowl champion, someone I really look up to for advice on coding and life etc. She will be the first female GM for sure.
@MannyElk – If you’re looking for hockey twitter, but also salads and interesting takes on pop culture, you should definitely follow Manny.
Manny is certainly a fun follow, and the others are great as well. How would you recommend hockey enthusiasts to learn more about the analytics behind the game, aside from reading all of the great content on www.qsao-queens.com and attending QSAO events?
I’d say read a lot. That’s what I did throughout my highschool years, I would just read and read and read until I finally felt comfortable presenting these ideas to a coach to volunteer. If you’re not comfortable learning coding just yet, learn everything you can about Excel or other data visualization software. Also learn to effectively communicate your ideas. I know that if I present my idea to the coaching staff as a bunch of numbers, they will not care. If I explain how the idea could be implemented and show them that it works in some setting, then it’s way more likely to be accepted. I think that’s a big problem with some analysts, they can be a little cantankerous or have a high and mighty attitude at times where it’s ‘them-vs-the-world,’ but that mentality won’t serve them well in life. So it’s really important to communicate these ideas effectively, in my opinion.
All the VANHAC talks are on Youtube (link to the playlist here) so watching all of those would be great. If you’re still in high school, or even University, find a way to work with them in any capacity. I started by running a Twitter account in Grade 11 for the Don Mills Flyers. From there, I met plenty of interesting people in the industry that I still keep in contact with. This gig helped me work for my high school team, which ended up being analytics.
Thanks for doing this Miles, looking forward to working with you in the future to help make the Queen's Men's Hockey Team even better.