NHL’s Enhanced Stats Released

2015 Coors Light Stadium Series - Los Angeles Kings v San Jose SharksThe NHL unveiled the first phase of their four-phase “statistical initiative”. As of today, there are now “enhanced stats” available on NHL.com that goes back to the 2010-2011 season.

This is the NHL’s first official foray into the world of hockey analytics. The field has been established and developed predominantly by hockey fans, who have used blogs for close to a decade to develop new ideas and knowledge pertaining to the game of hockey. Hockey analytics has been built within a commons-based peer production environment, which relies on the contributions of many without an overbearing hierarchical structure. Ideas about the game, how it’s played, and where the correlations are within traditional and advanced statistics are built within a large, highly collaborative network; a complete shift away from the traditional model of information production/consumption. Remaining as an ad hoc meritocracy, open to everyone and building off the ideas of one another have been key trademarks of hockey analytics, and continues to serve as a foundation for the field. Fans have relied on simple analytics tools and social media applications to develop new information and share knowledge across a collaborative network.

The league’s challenge now will be to find the right balance as a participant in the analytics world. They can be the official source of data, but they can’t overstep their boundaries and impose any sort of gate keeping in analytics. The flow of information and knowledge derived from the data cannot be disrupted in any way by the league.

The first thing they’ll need to do is improve their “enhanced stats”. The functionality of their website is nowhere near the quality of War on Ice and lacks some of the basic metrics. David Johnson has an excellent recap of where the limitations are of the “enhanced stats” and provides a few recommendations. Here’s hoping the NHL is planning to release additional data or are at least reaching out to the hockey analytics community for feedback. Everyone can benefit from having the NHL as a key source of information, so it’s in the NHL’s best interest to do what’s best for the entire fan community.

It would also be in the NHL’s best interest to partner with existing third-party websites like War on Ice and Behind the Net as well as mobile app developers. This could involve providing them with raw data sets and letting them decide how the data is presented, aggregated and visualized for fans. At the end of the day, fans are spending countless hours on third party websites looking at and thinking about hockey information.

It’s understandable that the NHL has renamed Corsi and Fenwick stats to “Shot Attempts” (SAT) and “Unblocked Shot Attempts” (USAT) respectively. The NHL is obviously trying to make the name of the stats easy to understand and self-explanatory so that it could appeal to more people. The problem is, there are thousands and thousands of articles written that use the traditional name of the stats. So if someone is just learning about the stats now, they’ll likely be diving in to the past content produced, forcing them to refer to SAT and USAT as Corsi and Fenwick. The NHL is trying to be a gate keeper here, but their attempts at changing names are pretty futile.

Lastly, the NHL has got to release its own version of CapGeek that provides player salary information. There is without a doubt that fans valued CapGeek as a source of information, which feeds discussion and new content (i.e., articles) on trades, free agency and team salary cap issues. Similar to advanced stat websites, CapGeek had fans spending hours a week looking at and thinking about hockey information. It was surprising to hear that the commissioner of the NHL wasn’t sure if fans cared about salary information, but I’m convinced there’s resistance from the NHLPA and player agents. Regardless, the NHL has to provide this information to fans, or watch as another third party becomes the source.

The field of hockey analytics has evolved and grown thanks in large part to the contributions of many. The rules and norms established by this collaborative network have been key to the growth of hockey analytics and need to be recognized by the NHL if they want to play a role. As encouraging as it is to see the NHL provide some of the advanced stats, it would be in their best interest to emulate some of the key characteristics of a “produsage” or commons-based peer production environment.

Past Articles

NHL Needs to Provide More Data (June 29, 2011)

Importance of Hockey Analytics II (May 5, 2014)

Keeping the NHL Data Open (August 15, 2014)

NHL to Provide Advanced Stats (February 5, 2014)

CapGeek, Hockey Analytics and the NHL’s Reluctance to Provide Information

Hockey in Society

CapGeek has announced that it would be ceasing operations as its founder and director, Matthew Wuest attends to some personal matters. CapGeek was the definitive source for NHL salary information used by fans, NHL teams and media outlets. It also provided interactive tools to determine if teams could take on player salaries, a cap calculator for armchair GM’s and what future rosters could potentially look like. It really improved the public’s understanding of the salary cap model and the numerous financial intricacies involved in building NHL rosters.

The website filled a need after the NHL implemented the salary cap in 2005. Team’s were no longer able to outspend one another and had to find a way to put together a roster with financial constraints. Team were on more of a level playing field, forcing fans to learn more about the cap and what implications it can have on their…

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Expanding the Scope: Insight from Gabriel Desjardins of Behind the Net

fehr-behind-netIt’s been great to see hockey analytics grow this year, but it’s still perplexing that more people aren’t looking past it and asking tougher questions about it’s relationship with other concepts and fields of research. The numbers and metrics are a part of a continuous discussion, which has intensified with more and more people joining in the discourse. For instance, possession stats have gained prominence, and that’s lead to more questions about the game. Projects tracking zone entry stats and puck retrieval stats will uncover new information, which will likely spawn off more questions. That’s the thing about analytics in any field…there is no finished product.

So if we look past the actual stats and the ensuing discussion, there’s still a lot to be understood about how exactly hockey analytics has impacted the different facets of the game (management, scouting, players, etc) as well as it’s relationship other fields such as information technology, business and society in general.

Behind the Net was one of the first websites that collected advanced stats, with its owner Gabriel Desjardins leading a lot of the online discussion in the early days. He sent out a series of tweets last week that gave some insight into hockey analytics, but also touched on some topics that have yet to be fully explored.

As we approach the trough of disillusionment for hockey analytics, here are a few helpful thoughts…

#1) Hockey insiders have been using “analytics” for decades. +/-, Sinden/Corsi shot/pass/touch counting, video aggregation. These stats had the imprimatur of cigar-chomping insiders, so nobody dug too deeply or cared too much

#2) One day, members of the general public found out what insiders had been doing and slowly worked through the value of this data. Somehow people popularizing the league’s internal metrics became outsiders as far as fans/media were concerned. It’s a classic obtuse battle of ideas. e.g. Obamacare was conservative for Romney but socialist for Obama. It took “analytics” predicting an unavoidable Leafs collapse to push people to the “Peak of Inflated Expectations”. It’s amazing – people promoted ideas the NHL used for decades w/o press caring but these ideas then needed to be proven publicly

#3) Now that analytics have been re-proven externally, teams have been getting PR boosts by announcing various hires but teams were already using analytics. So there’s no new benefit. Except I suppose people will expect the Leafs to benefit, hence the trough of disillusionment.

#4) Now here’s the missing piece: teams need to know how to interpret these stats and correctly use them to drive decisions. It’s statistical parallel to @Lowetide_‘s “saw him good” principle. Teams don’t understand regression will cut guy based on 3 games. Teams need to take long view to get analytics benefit and incentives don’t align. Today’s best GMs still only have 14-day outlook

#6) May see benefit for poorly-run teams [TOR, EDM] but the inflated expectations are that “stats guys” will take them on a 2015 playoff run. Unless @mc79hockey is making $1M a year, we need to seriously temper expectations

#7) There’s very little low-hanging fruit in analytics and most of it has been harvested in hockey. There’s no Matt Stairs or Roberto Petagine waiting to be freed. Helps that the KHL will put a pile of cash in your suitcase at the end of every game. Nobody needs to toil in the A for $75k/year

#8) The thing that initially annoyed me was Pierre Mcguire’s comments to @wyshynski about firing coaches for using analytics. But teams already sign and play guys because “Coach knew him in junior” or much worse.

Running the Edmonton Marathon

City of Edmonton

City of Edmonton

Completed the Edmonton Marathon on August 24, 2014. Easily the hardest thing I’ve gone through physically. Did not realize how much it takes out of you and the recovery needed afterwards.

I’ve been running consistently for a year. I aim for 10-20 km a week (a few times a week, somewhere between five and ten kilometers per week). I can pretty easily run up to 15 km at a 5:30 min/km pace without any issues. Early hours work best with two young ones at home.

Leading up to the marathon, the most I’d ever ran was a half-marathon about seven years ago. In hindsight, I was extremely unprepared back then but I finished the 21km trek in just over two hours. I remember being absolutely spent after that run, so I trained enough this time to avoid getting burnt out.

Along with running over the past year, I spent one morning a week at the local track merging in sprints, jogs and body weight exercises. Just picked up a couple tips online from this website that really helped build up the legs and core. Had ACL surgery in 2006, so I had to make sure the knee and supporting muscles were feeling fine.

Going into the race, I figured a pace closer to 6 min/km get me to the finish line. Objective was to finish but to maintain a good, reasonable, pace. Doing the math, it would take me around 4:12 to finish, but I also padded it and decided that a 4:20 to 4:30 would be reasonable.

The course started in downtown, went east towards Rundle Park, then back to downtown and then looped to the west end, and then finished in downtown. A very flat course, with no hills. Caught myself a few times looking out into the river valley. Click here for a map of the route: Edmonton_Marathon_2014.

I followed along with the 4:15 pace setter to start and see how things feel. The fellow keeping the pace was very social and passed on some great advice along the way. I stuck with them for the first 29 km very comfortably and was very relieved that I made it that far without any physical issues. Unfortunately, I had to take a bathroom break and never caught up to the group after that. Right around the 33 km mark was when the discomfort kicked in, making the rest of the run extremely tough. Thankfully, I pushed through, made it to the finish line in 4:32 and felt fine, all things considered.

Quick breakdown of my run, courtesy of Sports Stats:

10 21.1 35 42.2
0:59:49 2:06:16 3:37:40 4:32:50
5:59 5:59 6:13 6:28

Average finish time was 4:06:51. Total of 542 participants.

Legs and back were pretty stiff after the run. Soreness stuck around for about 4 days. Took two weeks off from any physical exercise to fully recover, which I’m glad I did. Muscles felt very shaky for days, so I decided I didn’t want to risk any serious injury. Also felt pretty nauseous for a day, but some sleep and a good diet took care of that.

Thought the event and route were well planned. Really can’t say enough about the volunteers. From handling the race kit pick-ups, to the water stations, to the signs along the way, the volunteers really made the event a success.

Congrats to Arturs Bareikis for winning the Marathon. He completed the route in 2:27:46 with an average pace of 3:31 min/km. Just ridiculous. You can track his journey to the Olympics on his blog.

Related Links:

McGrath runs personal-best in Edmonton Marathon, but still finishes second – Edmonton Journal

Reporter on the Run (Series) – Otiena Ellwand of the Edmonton Journal

Edmonton man runs five marathons for his aunt – Edmonton Journal

Runners, organizers welcome Edmonton marathon downtown route change – Metro News


Diffusion of Hockey Analytics

Hockey in Society

Applying Everett Rogers’ Diffusion of Innovation theory to understand the adoption of hockey analytics

As fans, we all watch, follow and engage with the game very differently. Hockey analytics really is a supplement to our experience with the game, much like gambling, fantasy league and video games. What a person pays attention to during a game depends on their own experience, including their biases and preferences.

Aside from the information it’s creating and the impact it’s having on the game, hockey analytics is first and foremost a method of engagement with the game. Fans are far more than passive consumers and have used the communication technology available to fully immerse themselves in an active, participatory culture.

Having said that, hockey analytics is an innovative way to understand the game as fans try to detect some sort of meaningful patterns. Again, it’s not for everyone, but the fact is analytics, especially the…

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Beyond the Stats: An Interview with Extra Skater’s Darryl Metcalf

Hockey in Society

Chicago Blackhawks v Los Angeles Kings - Game Four Los Angeles Kings

The popularity of hockey analytics continues to grow as fans, teams and the NHL embrace new methods of measuring team and player performance. The uptake of analytics is dependent on the individual doing the analysis, as each person has different opinions and biases regarding what impacts a game result and what doesn’t. As a result, a number of websites have emerged providing various levels of data and analysis, putting the onus on the end user to interpret it as they please.

It’s important to note that fans in particular have lead the charge when it comes to developing and discussing new ideas regarding the game. The online environment has been critical for the growth of hockey analytics as fans connect online, publish ideas and develop the knowledge that surrounds the game. In recent years, a number of data visualization tools such as Super Shot Search and Shift…

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Random thoughts on hockey analytics

Couple tweets I sent out a few weeks ago after Joffrey Lupul of the Toronto Maple Leafs had this to say regarding data analytics in hockey:

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