Talking Oilers and Analytics on The Lowdown with Lowetide (TSN 1260)

I joined Lowetide on Monday morning to talk about the Oilers and how they should better integrate analytics. Full audio is here.

Couple notes:


Oilers and Analytics 

A couple thoughts on analytics, and how best to integrate it into hockey operations.

With the Oilers cutting ties with analytics consultant Tyler Dellow, the club has an opportunity to re-set its current approach to analytics going forward. Now it was my hope that Tyler’s role would’ve expanded from a consultant position, perhaps into a director type, who would then lead a group of analysts to delve into various topics. It was my hope that the Oilers would’ve applied a more complete analytics strategy that could support and influence all aspects of hockey operations including on-ice tactics, player personnel decisions, drafting and salary cap matters.

And let’s not kid ourselves: analytics is going to have a role in professional sports, but its exact definition and scope is going to vary depending on the sport, league, team and goals. Analytics is becoming more and more ingrained in all industries whether it is healthcare, oil and gas, government, and the thought of the value of analytics fading in hockey is completely bogus.

Analytics should never be treated as some magic bullet or switch that an operations manager can just flip and make things happen. Analytics is a continuous process, one in which a business need or goal leads to questions. From there, an organization looks to its data to see what can be answered, and what other data can be collected and refined to potentially answer that question. From there, analysis of the data is done, which leads to discussion with the operations side and, quite often, leads to more data collection/analysis/discussion.

Before all of this is even thought about, teams like the Oilers have to treat analytics as a new concept that has to be assessed carefully before it’s legitimately integrated. And like most organizations, the Oilers need to look at three areas: people, process, technology (or tools).


  • Do you have the right skills in your organization that can support a team of people whose focus it will be to analyze data?
  • Do you have the right type of managers that will keep analytics top of mind when reviewing the operations they oversee?
  • Are people willing to learn the skills needed to either work with or within an analytics team?


  • How will the organization facilitate the work of the analytics team?
  • Regular presentations to management? Crossover meeting between the analytics team and, say, the coaching staff?
  • Do these collaborations need to be formalized or do you let the analytics team set up ad hoc meetings and working groups?


  • Do you have the necessary tools for your analytics team, or is there a chance you’ll have to invest in some additional applications?
  • It would be safe to assume that your analysts would dictate what tools are used, and the organization has to be prepared to support them.

One thing that I hope the Oilers consider doing is finding a way to tap into the knowledge of the fan community, especially those that spend hours analyzing data and publishing their work online. And this really isn’t a long shot for the team. Keep in mind, the Oilers have put together a volunteer advisory group in the past to support hockey operations and they’ve also hosted a Hackathon competition where they posted a question, released a pile of data and rewarded the best solution (nice work Parkatti!). What I think the Oilers can do here is enhance these two concepts and turn them into actual, formalized programs that can be sustained and provide value to the club.


One thing I have trouble wrapping my head around is when NHL teams hire a consultant or two to support their analytics process. Above is a chart from Gartner, which does a really nice job breaking out analytics into four types: Descriptive (what happened?), Diagnostic (why did it happen?), Predictive (what will happen?) and Prescriptive (how can we make it happen?). What we see without even caring about value and difficulty of each type are complex tasks that each require more than just a data analyst or consultant.

Looking at this through a hockey lens, the first type would be simple reporting, as in how many goals happened for and against. With Diagnostic, you would start looking into shot shares/location/player deployment/line match-ups, etc, basically looking at the things that you think do a good job at predicting goals. These first two types of analytics have become pretty standard things in the hockey world, and are published daily by fans online. But if you’re running a team, your hockey operations department could be looking at more than just goals for instance and the things that lead to goals. Maybe you want AHL player data, or a better way to track the passes that lead to shots. And if that’s the case, you need a way to gather and refine that data, which could require manual tracking and someone with programming experience. If your club wants the findings shared in a certain way, you may need someone who specializes in reporting or even dashboard reporting. And it’s also here that you may need someone who can break down video and compile their findings quickly for the coaches or management to use.

And when you start getting into the prescriptive analytics, you’ll absolutely need someone on the analytics team that has coaching experience or someone that can marry the data to the actual on-ice plays to make sense of it and provide recommendations. Reviewing these types of analytics and the potential value it can bring to a team, it would be imperative that a team like the Oilers put together a complete analytics team. This should include a director type, along with analysts well versed in reporting (dashboards), programming and on-ice coaching. Teams like Toronto, Florida and New Jersey have this structure, which should become the norm among NHL clubs soon.

It’ll be interesting to see what the Oilers do in regards to their approach to analytics. In my experience, analytics is one of the many tools that business leaders rely on to make informed decisions and is part of a holistic approach to finding success. The purpose of analytics, especially in a business setting, is to provide evidence, drive discussion and support the corporate goals. And it can only be leveraged to its full capacity when there’s complete support, at the strategic level and the operations level.

Curious to hear the thoughts of others on this one. Every industry is different, so I’d be interested in hearing how others have implemented/experienced analytics.

Also joined Lowetide on TSN 1260 to talk about this further. Audio is here.

The Oilers Offensive Zone Tactics

This past week, Ryan Stimson of Hockey Graphs published a very insightful article where he attempted to quantify two offensive zone strategies that teams rely on, focusing on the tactics used by the San Jose Sharks and Los Angeles Kings this past season. This was following some comments made by Kings assistant coach Davis Payne, who presented at a coaching clinic in Buffalo. The full article is a must-read for anyone interested in team systems and analytics.

Two tactics, the Low-to-High-to-Net Attack, where assists come from point shots, and the Behind-the-Net attack, where a play is developed from behind the goal line, are explained extremely well in the above article, including plenty of video to explain the tactics and the pros and cons for both plays.

Since the passing data is publicly available, I figured it would be worth digging into the Oilers numbers and verifying what we’ve heard the coaching staff discuss this past season, including McLellan’s concept of volume shooting.

Full article is at The Copper & Blue.

Talking Lucic/Hall, Puljujärvi, Goalie depth and more on The Lowdown with Lowetide (TSN 1260)

Joined Lowetide this morning on TSN 1260 to talk Oilers. Full clip is below, starting around the 40 minute mark.

Couple notes:

  • Some useful dashboards that compare Hall to Lucic. They’re both good players who can play in your top 6, but I’d take Hall over Lucic any day because of his style of play, production and long term outlook.

This one is from Ryan Stimson of Hockey Graphs:

Dashboard 1 (1)

And this one is from Own the Puck:

Story 1 (2)

  • Definitely not a fan of the Gustavsson signing. Dug into his numbers last week.
  • The rebound analysis that I referred to is here.
  • And the positives I found from last season are written up here.


Goaltending Might Be An Issue for the Oilers Next Season

Dashboard 1
Heading into the summer, it was fairly obvious that the team would need to find a dependable backup to play behind Cam Talbot and push young Laurent Brossoit down to Bakersfield for additional seasoning. Although Brossoit had put up some nice numbers at the AHL level, his showings in Edmonton were not very good, as the young prospect appeared in five games, finishing 0-4-0 with a sub-standard 87.18 save percentage at even-strength (Source: Corsica Hockey)

On July 1st, the Oilers did find a backup in 31-year old Jonas Gustavsson, who played with the Bruins last season going 11-9-1, with a 91.42 save percentage at even-strength. Among the 55 goalies who played at least 900 minutes last season, or around 20 games, similar to Gustavsson, the Oilers newest addition ranked 47th when it came to save percentage at even strength, the average of the group being 92.46. The season prior, Gustavsson only played in seven games, with Jimmy Howard and Petr Mrazek taking on the bulk of games, and did show well, but it’s hard to make any large conclusions based on such a small sample size.

Full article is at The Copper & Blue.

Deploying Adam Larsson

Something to consider now is how defenceman Adam Larsson will fit into the Oilers in terms of pairings, deployment and match-ups. Judging by some of his underlying numbers, Larsson has performed as more of a shutdown type defencemen in New Jersey that starts a lot of shifts in his own zone, typically against the best competition.

To put Larsson’s deployment in New Jersey into perspective, I’ve generated a player usage chart from Corsica Hockey to show how he measured up against his teammates last season at even-strength. The x-axis is the Zone Start Ratio (ZSR), which is the percentage of non-neutral zone starts that are offensive zone starts. The y-axis is the Time On Ice Quality of Teammates metric (TOI.QoT), which is the weighted average time-on-ice percentage of a player’s teammates. The bubble size is the individual player’s Time On Ice Percentage, which is the percentage of a team’s time-on-ice played by a player. And the coloring of the bubbles is the individual player’s Corsi relative to his teammates. (Source: Corsica Hockey).

Full article is at The Copper & Blue.

Talking Oilers on the Arctic Ice Hockey Podcast

Joined Alan and Phil from Arctic Ice Hockey to talk Oilers this past weekend. Full podcast can be found here (starting around the 8:00 minute mark after the intro):

Topics included:

  • Oilers drafting Jesse Puljujärvi and what to expect from the latest group of draft picks
  • Trading Hall for Larsson
  • Signing Milan Lucic
  • What to expect from Leon Draisaitl this coming season
  • RNH’s importance to the club
  • The current defence core

Thanks again to Alan and Phil for having me on.