Fixing the NHL’s Enhanced Stats

b65595b0-6458-11e5-91e8-1be7ed6137db_75The NHL’s foray into providing advanced stats to fans has been an absolute failure. They’ve made a heavy, long-term investment in the technology and development of the website, but they’re still not providing their fan base any sort of value.

I wrote an article when the advanced stats were first released by the NHL in February of this year, believing that the NHL was on the right path, but cautioned where the pitfalls would be if they didn’t approach it differently. Hate to say it, but everything has gone wrong.

Travis Yost put together an excellent summary of the problems the NHL has had with their advanced (enhanced) stats. Based on my own experience of the NHL’s website, and how others have experienced it, I’ve come down to this: The NHL does not completely understand the field of analytics and what their fans want, and as a result, the features promised by the NHL do not meet expectations.

So what’s the problem?

From a high level, the problems the NHL is facing are similar to what other large-scale IT projects go through. This would include things like substandard requirements gathering, poor project planning and not enough customer/user engagement. But taking a step back, I see two major issues that are at the foundation of the problem. Not saying resolving these two issues will solve everything. But improving on it can impact the NHL’s overall strategy when it comes to advanced stats and future projects.

First off, the NHL does not truly understand what analytics is, what it’s for and how it’s used by their fans. Analytics are more than just stats. It’s a process, continuous in nature, that spurs new ideas, new questions and new understandings of a topic. It’s about collecting raw data, aggregating it into useful metrics, finding patterns, testing it’s validity/reliability and applying it in some way to a real problem. For people like me, websites like War on Ice have done most of that and have an easy to use tool for me to gather the data needed to answer my questions. On top of that, the website provides all of the raw data, so I can take it, integrate it into other software and apply my own queries and models.

To provide stats to a fan base that’s eager to discover new information and share their findings with others, the NHL has got to provide the outputs that reflect the creative nature of fans. Infographics are great, and the NHL does a nice job producing them. But they don’t provide the ability for fans to drill into a particular stat seamlessly to answer their next question. If the NHL wants to be the primary resource for advanced stats, they need to stop providing their data as reports and instead deliver the data with interactive, customizable tools.

Secondly, the NHL has viewed, and continues to view, fans as simple consumers of their products. The league relies on the traditional model of consumption (i.e., the NHL provides entertainment, fans buy tickets and merchandise) and develops their services and overall marketing strategy accordingly.

The problem is that the traditional model of consumption cannot apply when offering enhanced stats. The fans that are looking for data are there to not only consume, but to also build on their findings and share with others. Consider the thousands of artifacts created daily by fans (blog posts, videos, photos, etc), which in turn promotes the league, its teams and its players.

The growth of analytics, including the ideas, the knowledge building and the tool development, is caused in large part by the overall evolution of the fan community. We’ve seen how communication technology such as social media, blogs and mobile phones, have changed fans from simple consumers to “produsers” (Bruns, 2008) that have an influence over the information and knowledge surrounding the game.

Suggestions

If the NHL is serious about playing a role in hockey analytics, they need to adjust their current strategy with a couple things in mind.

  • The NHL needs to recognize where the existing gaps are in the analytics field that would improve their fan’s experience. Right now the most pressing issue is the actual collection of the data and the data quality. The current public websites such as War on Ice and Hockey Analysis used scraped data from the NHL website. This means that the data does have some accuracy, but it would be vastly improved if the NHL took the lead in collecting and publishing real time data. This would include shot location data, player tracking and shift tracking.
  • The NHL must also become a collaborative partner that supports private development of applications that would publish the data. The NHL does not need to replicate War on Ice. Instead, it would be in their best interest to support these types of websites knowing full well that their fans will be using the applications and generating new NHL-related content. And judging by the “visualizations” that the NHL currently provides, they need to leave the creativity to fans and private developers.

Even though the NHL is struggling with their enhanced stats page, and appear to be tied to their agreement with SAP, there is hope. The NHL can definitely have a role in the field of hockey analytics, but they must first understand the concept of analytics and recognize the importance of fans as not only consumers but also sources of hockey information and knowledge.

Related:

NHL Enhanced Stats Released – The SuperFan (February 22, 2015)

SuperFan 2.0: Exploring the produsage qualities of hockey fans (March 23, 2012)

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In Hall We Trust

Source: EdmontonOilers.com

Source: EdmontonOilers.com

I can’t believe I have to write this.

Taylor Hall is one of the top players in the game today. Despite playing for one of the worst franchises in recent history, Hall has been a very productive player. He’s about to complete his fifth year in the NHL, playing for his fourth coach, and there appears to be some question about his value.

To judge a player, we can supplement what we see on the ice with both traditional stats as well as some of the more modern metrics (i.e., posession, scoring chances, etc).

From what I’ve seen, Hall is an absolute beast when it comes to attacking the opposing net. He’s very good along the boards, excellent at gaining the zone, not afraid to take a hit, and he can finish. Now for the numbers.

Overall

GP G A PTS PPG PPA SHG SHA GWG PIM SHOTS
2010-11
65
22
20
42
8
3
0
0
4
27
186
2011-12
61
27
26
53
13
8
0
0
7
36
207
2012-13
45
16
34
50
4
10
0
0
4
33
154
2013-14
75
27
53
80
7
10
0
1
1
44
250
2014-15
50
13
23
36
3
3
0
0
0
40
146
Total
296
105
156
261
35
0
16
180
943

Not bad right? 261 points is second only to Tyler Seguin (279 points) of the 2010 draft class, but keep in mind, Seguin has played 56 more games (Source: HockeyDB). In 2012/2013, he was ninth overall in scoring. In 2013/2014, he was sixth in total points, behind Crosby, Getzlaf, Giroux, Seguin and Perry.

Even Strength

The true value of a player is how well they do at even strength. Here’s a look at how he’s done, as well as the number of points per 60 minutes at 5-on-5.

Season
Games
Goals
Assists
Points
G/60
A/60
P/60 
TOI/Gm
2010-11
65 10 15 25 0.6 0.9 1.6 14.8
2011-12
61 13 18 31 0.9 1.2 2.1 14.4
2012-13
45 12 21 33 1.1 1.9 3.0 14.5
2013-14
75 16 37 53 0.8 1.9 2.8 15.2
2014-15
50 6 18 24 0.4 1.4 1.8 15.9
Total
296 57 109 166

In 2012-12, Hall was sixth in the league in points-per-60  (at even strength) behind guys like Crosby, Toews and Staal. In 2013-14, he was sixth again, behind guys like Getzlaf, Perry, Seguin and Benn. In terms of productivity at even strength, Hall is one of the best in the NHL.

You can also average his assists per 60 & points per 60 over 4 years (2011-15) to see that he’s the 4th best playmaker & 8th overall points producer in the NHL (thanks to Walter for finding that).

Advanced Stats

Since entering the league, Hall has been given a lot of offensive zone starts and has delivered. He regularly sees the top competition, but has managed to produce at a very decent clip. What we can also glean from his advanced stats is how vital Hall is to the Oilers success. For instance, the Oilers are more likely to have possession of the puck when Hall is on the ice. The team typically gets their decent share of shots and scoring chances when Hall is on the ice, and the team doesn’t do nearly as well when he’s on the bench. It should also be noted that Hall’s shooting percentage is usually pretty consistent, and its drop may be the reason why he has struggled this season. I think it’s safe to assume that shooting percentage will get back to normal very soon. I’ve included a full table of his stats in the Appendix.

Here’s a visual of Hall’s deployment and performance last season. You can see here, and in his other four seasons (Appendix below), that he gets a decent amount of offensive zone starts,faces tougher competition, and still manages to produce. (Source: Hockey Abstract’s Player Usage Charts)

Oilers 2013-2014

Trade Hall?

If the right player becomes available, every single player on this roster should be made available. The Oilers are clearly in need of a few defensemen, so it shouldn’t surprise us to hear trade rumors involving Hall. However, if there is any thought of moving Hall for any other reason (i.e., “character” issues, “winning culture”), then a few things need to be considered.

To move Hall, the Oilers would need a player that would take over the minutes from Hall AND produce at that clip. Unless a player coming back is someone that can crack the top 10 in points-per-60 at even strength, you’d be nuts suggesting Hall be moved. Benoit Pouliot has been a fantastic addition, but he would not be able to match any of Hall’s point totals. This roster is weak enough as it is, so moving away a legitimate NHL player, at a very cap friendly salary, is completely absurd.

I read a couple comments on Twitter questioning Hall’s ability to stay healthy. First of all, this is professional hockey. Crazy shit can happen in a split second when you’re cruising around the ice on sharp blades and taking regular contact. And we knew before the Oilers drafted Hall what kind of player he was going to be: hard skating, drives to the net, a bit wreckless, but effective at carrying the play in the right direction. If playing a little on the edge is what will keep Hall productive, then we have to live with it.

Final Thoughts

I will say that my perception of Hall changed this season, not because of his performance, but because of the emergence of RNH. Going into the season, I saw Hall as the face of the franchise; someone that would be captain in the next few years. Now, I still see Hall as a vital part of the club, but not nearly the same captain/franchise material as RNH. This might be a reason why others see Hall as expendable. Just a thought.

Also, the Edmonton Journal needs to stop with their ridiculous polls. It’s bad enough that a recent one found that people would trade Hall, but then they had to mention Hall’s twitter account when they tweeted their findings, just to make sure he knew how fans felt about him. Classy.

Being a top player, Hall will always have misinformation about him being published and spread. It’s always important to question the content, who is saying it, and the timing, Really, as long as the Oilers keep losing, the rumours will continue,..that’s just how it works. And let’s not twist Hall’s placement on the second line with Lander and MIller as some sort of demotion. That to me is a sign of depth, done in large part by the signing and performance of Pouliot.

Recommended Links

RE 14-15 Taylor Hall: Midnight Rider – Lowetide

Appendix

Below are his stats using the Hockey Abstract’s Player Usage Charts.

Oilers 2010-2011

Oilers 2011-2012

Oilers 2012-2013

Oilers 2013-2014

Advanced Stats Summary for Taylor Hall

Source: War on Ice

2010-11 2011-12 2012-13 2013-14

2014-15

Gm

65 61 45 75 50
G 10 13 12 16 6
A 15 18 21 37 18

P

25 31 33 53 24
TOI/Gm 14.8 14.4 14.5 15.2 15.9
PRODUCTIVITY

G/60

0.6 0.9 1.1 0.8 0.4

A/60

0.9 1.2 1.9 1.9 1.4
P/60 1.6 2.1 3 2.8 1.8
Penalties Drawn (Diff) 21 6 10 8 -4

PDO

99.5 100.6 100.7 100.7 100.4

PSh%

6.8 9 10.2 9.6 6.4
ZSO% 51.2 56.7 54 56.6 55.9
ZSO%Rel 2.1 9.4 9.2 17.4 9.1
POSSESSION, CHANCES, SHOTS

Scoring Chances For %

48.1 51.3 49.7 46.1 49.4

SCF% Rel

5.5 5.4 7.8 1.6 6.2
Corsi For % 48.8 52.3 50.4 44.4 51.1
CF% Rel 4.7 6.5 8.6 0.4 4.2
Shots For % 47.1 51.1 51.8 45.9 48.1
SF% Rel 2.5 5.4 10 2.2 1
Goals For % 45.7 52.6 53.8 47.8 49.2
GF% Rel 1.7 9.7 10.5 8.8 13.7

.

Productivity of Players Under Eakins and Nelson

Source: Winnipeg Free Press

Source: Winnipeg Free Press

In my last post, I focused on the longest losing streaks each coach has had behind the bench this year. The purpose was to find out why Nelson’s losing streak was somewhat dismissed, while Eakins losing streak received a far greater backlash. Eakins’ 11-game skid had some decent underlying numbers at 5-on-5, but had some sketchy goaltending and a weak powerplay and failed to have any positive results. Nelson just finished off a 7-game streak, where they were absolutely lights-out on the powerplay, but had some troubling underlying stats at 5-on-5. My guess is that the success of the powerplay, and the point production of the young guns like Eberle, RNH and Yakupov gave the perception that Nelson was doing a better job.

I received a comment that suggested that individual players have benefited from the coaching change and their production has been better under Nelson. At first glance, it appears to be true. Eberle and RNH in particular have been outstanding over the past few weeks, with a large chunk of their points coming on the powerplay. Make no mistake, Nelson has done very well with the man advantage, something he was known for at the AHL level, and deserves full credit for its success. My take, however, is that 5-on-5 play is much more important, so I decided to take a look at the productivity of players at even strength under the two different coaches.

Please note, I exclude the five games that MacTavish was behind the bench in all of my comparisons involving Nelson. I’ve included in the list below the players who played under both coaches. (Source: War on Ice)

Eakins Nelson
Name

Pos.

Games

P60 CF% TOI/Gm Games P60 CF% TOI/Gm
Ryan.Nugent-Hopkins C 29 1.97 51.83 15.79 37 1.73 50.57 15.00
Nail.Yakupov LR 31 0.93 48.90 12.47 36 1.51 43.48 13.26
Taylor.Hall L 25 1.65 53.15 16.04 14 2.31 50.38 14.86
Jordan.Eberle R 30 1.82 53.97 15.41 37 2.24 50.29 15.23
Benoit.Pouliot L 20 2.19 51.47 10.95 29 1.44 51.23 12.96
Boyd.Gordon C 27 1.11 46.68 10.02 37 0.63 42.02 10.33
Luke.Gazdic L 10 0.00 45.37 7.03 19 1.33 46.30 7.13
Matt.Hendricks LR 27 0.68 47.54 9.80 35 0.87 43.63 11.80
Leon.Draisaitl CL 31 0.88 52.76 11.05 2 5.73 56.76 10.47
Tyler.Pitlick RC 7 0.68 51.54 12.57 2 0.00 30.43 10.70
Iiro.Pakarinen RL 5 1.65 50.00 7.25 12 0.00 47.17 10.79
David.Perron RL 31 1.73 52.01 13.43 2 2.49 57.14 12.07
Teddy.Purcell RL 31 1.23 54.70 12.56 37 0.85 46.23 13.37
Justin.Schultz D 30 0.92 50.99 17.32 37 0.44 50.58 18.59
Jeff.Petry D 30 0.33 53.00 17.97 24 0.74 43.09 16.93
Keith.Aulie D 12 0.00 51.60 12.59 10 0.45 36.86 13.28
Mark.Fayne D 31 0.53 49.49 14.52 37 0.22 44.19 15.05
Andrew.Ference D 28 0.24 48.45 18.04 37 0.94 41.98 15.46
Oscar.Klefbom D 10 0.33 53.52 18.34 37 0.97 50.91 18.40
Martin.Marincin D 12 0.34 51.29 14.56 20 0.00 49.00 16.07
Nikita.Nikitin D 22 0.53 50.57 15.46 15 0.27 45.83 14.83

Looking at the point production (points per 60), the two players that saw an increase of their 5-on-5 production under Nelson are Eberle and Yakupov. Hall’s numbers increase, but that may have been because he was banged up early in the season. What’s surprising is the decrease in productivity for players like RNH, Pouliot, Gordon, Purcell and even Schultz. What’s troubling is the decrease in the possession numbers (Corsi For %) across the board. We are seeing that the team does struggle with possession in all score situations (whether they’re trailing, leading or the game is tied) under Nelson, while Eakins had something figured out when it comes to 5-on-5 play.

And here are the players who were coached by one and not the other. Included are guys like Lander, Roy and Klinkhammer who have all done relatively well with Nelson behind the bench, but still struggle possession wise.

Eakins Nelson
Name

pos

Gm P60 CF% TOI/Gm Gm P60 CF%

TOI/Gm

Anton.Lander C 28 1.19 48.29 10.82
Derek.Roy C 37 1.67 45.93 13.63
Ryan.Hamilton L 16 0.32 40.99 11.54
Rob.Klinkhammer L 32 0.48 46.22 11.67
Matt.Fraser LR 28 1.21 41.71 10.62
Drew.Miller RC 3 0.00 53.25 11.19
Jordan.Oesterle D 6 0.75 49.64 13.42
Will.Acton C 3 0.00 44.68 9.22
Bogdan.Yakimov C 1 0.00 61.54 10.05
Mark.Arcobello CR 31 0.89 49.86 13.10
Steven.Pinizzotto R 13 1.20 43.51 7.68
Jesse.Joensuu RL 20 0.63 45.93 9.57
Brandon.Davidson D 3 0.00 42.86 10.52
Darnell.Nurse D 2 0.00 56.36 15.21
Brad.Hunt D 6 0.00 50.00 15.82

What’s become apparent is that individuals are producing more points, but it’s due in large part to the successful powerplay. Stripping the powerplay away, however, gives us a better assessment on how the team is doing for the majority of the game. In this case, the production has increased for some and decreased for others. When it comes to possession, which is a key indicator of team success, the entire team is struggling mightily.

Both Eakins and Nelson are qualified NHL coaches, having found success at the AHL level, and will likely be employed in some capacity next season in the NHL. Nelson should definitely be considered for the OIlers head coaching position next season along with other experienced coaches available this summer. The problem is that the Oilers are struggling to assemble an NHL caliber roster, and until they do, it really won’t matter who the coach is next season.

Talking analytics and advanced stats on Inside Sports

Had the opportunity to be a guest on Inside Sports last night. Host Reid Wilkins invited me on to discuss analytics and the enhanced stats that have been released by the NHL.

You can hear the full interview here (starts at 2:30):

Couple notes I want to add:

  • You can access the enhanced stats on NHL.com. Keep in mind, this is the first phase of the NHL’s stats initiative. We can expect some data visualization tools and player tracking in the near future. [NHL.com]
  • There are tons of good articles that provide an introduction to analytics and advanced stats. This one from Sports Illustrated gives an excellent primer on Corsi, Fenwick, PDO and QualComp.
  • The best website for advanced stats is War on Ice. Has everything you need, excellent functionality (i.e., filters), easy to use, and has an excellent glossary. HockeyStats.ca is also pretty solid, as well as Nice Time on Ice. New data visualization websites are popping up every week, so it’s worth keeping an eye on.
  • A few of the original blogs/websites that pushed the growth of analytics were Behind the Net, Irreverent Oiler Fans, Objective NHL and mc79hockey.com. A couple of those sites have been taken down as they’ve been hired by NHL clubs.
  • Reid and I briefly touched on Taylor Hall and how his possession numbers align with his boxcar stats. Ryan Batty of the Copper and Blue had an excellent piece from last season that covered this: Taylor Hall – Points vs Corsi.
  • We also discussed shot quality, which I would argue is good to know, but doesn’t predict future outcomes as well as Corsi/Fenwick. This piece by Eric Tulsky at NHL Numbers explains the correlation differences.  Nick Mercadante of Blue Shirt Banter also has a solid post on this.
  • If you’re wondering why Boyd Gordon is the Oilers MVP, please read this excellent piece: Boyd Gordon – Superhero.
  • Shawn Horcoff was accustomed to doing a lot of the heavy lifting as an Oiler. Prime example of a solid two-way centerman who went up against the best players in the NHL and started often in the defensive zone.
  • My research at the University of Alberta focused on  hockey fans and their online collaboration to develop new information and knowledge pertaining to the game. You can read more about it here, or access the full research paper. Also recommend reading my post Finding the SuperFan.
  • Michael Parkatti and I put together a public lecture at the U of A last year on hockey analytics. You can watch the full session on Livestream.
  • I touched on a few of the reasons why analytics was significant and how fans are really the drivers of new information and knowledge. More of my thoughts can be found here: Importance of Hockey Analytics II.

Thanks to Reid for having me on his show. Definitely a unique experience!

Looking Back at the Oilers’ 2005-2006 Season

img003Being a terrible hockey team for almost a decade impacts a lot of things. The low morale of fans, the constant trade rumors and bogus narratives, and the negative perception of management and owners are all tied to loser franchises. These are things that can easily be reversed if the team starts winning, but unfortunately, that isn’t happening any time soon.

And as the playoff drought continues for the Oilers, the history of a franchise also starts to get diminished. There’s this notion that the Oilers have been bad far past the 2006 cup run. The narrative makes sense: they were the 8th seeded team that barely made the playoffs in 2006 and beat out Detroit (1st), San Jose (5th) and Anaheim (6th) to get to game seven of the finals. Following the loss to the Hurricanes, the team went on to missing the playoffs nine straight years. Add it all up, and you could safely assume that the 2006 run was a complete fluke.

What gets overshadowed by the Oilers remarkable playoff run in 2006 is their regular season performance. While it’s true that the team finished 8th and clinched a playoff berth in the last week of the season, there are some underlying numbers worth highlighting. Here’s their overall record

GP W L OT PTS PTS% VS WEST VS CEN VS NW VS PAC
82 41 28 13 95 0.574 38-25-9 10-6-4 15-15-2 13-4-3

That Northwest division was quite the killer that season. All five teams had points percentages above 0.500. No other division was as this tight. The Oilers needed 95 points to qualify for the playoffs and  were only four points back of 5th place San Jose. The club ranked 14th on the powerplay (18.1%) and 8th on the penalty kill (84.1).

Here’s a high level snap shot of the Oilers’ advanced stats from the 2005-2006 regular season. I took into account all situations and found a comparative team from the 2013-2014 season based on rank. Regular season shot attempt data is worth reviewing, as it’s been a pretty good predictor of championships.

All Situations

Corsi For % of total Fenwick % of total Shot Differentials Total Percentage of shots On ice shooting percentage On ice save percentage PDO Off Zone Starts

Rating

52.2 53.7 347 53.8 10.2 88.4 98.6 53.1

Ranking

6th 3rd 3rd 3rd 17th 30th 26th

6th

2013-2014 Comparison St. Louis Chicago LA LA Montreal NYI Calgary

Boston

 Source: War on Ice

The Oilers put together some fantastic numbers over a full season, and compare well to some of the more recent top teams. The Oilers were a strong possession team over 82 games and had the sixth highest offensive zone starts. The team allowed the fewest shots in the league, but had the worst on-ice save percentage. That of course impacted the PDO, which was one of the lowest in the league. Worth noting that the Avalanche, who finished 7th overall, had the second highest on-ice shooting percentage (11.4%), while the 6th seeded Ducks combined their excellent possession stats with the sixth highest on-ice save percentage (90.9%).

Chris Pronger was instrumental in the team’s possession numbers, but the Oilers had a very well constructed roster that started with talent down the middle. They had the second best team-faceoff percentage that season (53.4%), with Horcoff and Stoll both finishing with 65+ points. The wingers took close to half of the total shots, with Smyth and Hemsky finishing with 66 and 77 points respectively. And of the top six defencemen based on total ice time, only one was under 30. Not bad roster management. Source: Hockey Reference

The weakness of the Oilers that year was definitely in goal as the club struggled all season to get consistent performances. The goaltending was pitiful with no clear cut starter all season. Only two shutouts registered in 2005-2006, while the Flames got 10 from their keepers. It was finally at the deadline that Lowe acquired Roloson from Minnesota for a first round pick and sent away Morrison (waivers) and Conklin (AHL).

Player

Games

Minutes Wins Losses T/O SV% GAA

SO

Jussi Markkanen

37

2016 15 12 6 0.880 3.12

0

Mike Morrison

21

892 10 4 2 0.884 2.83

0

Dwayne Roloson

19

1163 8 7 4 0.905 2.42

1

Ty Conklin

18

922 8 5 1 0.880 2.8

1

 Source: Hockey Reference

Piecing together these stats is really just a way to get a fair assessment of what the team actually was ten years ago. The narratives grow and evolve over time depending on the context, so it’s critical to ground our understanding of the game in some degree of quantitative evidence. A blend of the advanced stats derived from analytics with the standard boxcar numbers of the players give a much better assessment of the team’s regular season success.

If there are additional stats or stories from that season worth mentioning, let me know.

NHL to Provide Advanced Stats

The NHL recently announced that they’ll be adding some of the “advanced” stats to their website for fans to access. These stats have really been developed by online hockey fans since about 2005 thanks in large part to people like Gabe Desjardins and Vic Ferrari, whose websites developed the core principles of hockey analytics. Over the past few years, the field of hockey analytics has grown to the point where many of those who pushed the discussion on analytics are being hired by NHL teams. The field is still in its infancy as the data collection tools and application of the analysis to game situations is still developing.

The NHL involvement with collecting data and publishing it on their website has been long overdue. While they continued expanding their traditional stats, fans developed their own websites and blogs that collected game-data (using NHL.com) and aggregated advanced stats. Fans worked outside the traditional model of information consumption and became sources and distributors of information themselves. Blogs especially played a critical role as fans discussed the stats, collaborated and developed strong information networks.

What the growth of hockey analytics has confirmed:

  1. Compared to any other type of fan (i.e., comic book, movies, celebrities, etc), sports fans spend the most time and energy on their fandom. They are connected before, during and after games by reading articles, playing fantasy league, consuming content (TV, radio, web). They’re a big reason why mobile technology is the beast that it is today.
  2. The web is a magical place that allows human beings to develop social networks to break down the barriers to information. If people want information, they will get it. The web is just designed that way.
  3. When an online community is connected to one another by something that they are truly passionate about, they’re extremely generous with their time and energy. Hockey bloggers are intrinsically motivated to not only produce content, but also share their support to others.

Knowing what we know about online hockey fans, it would be a huge mistake for the NHL to charge fans any sort of fee to access hockey data. The league has already taken steps to restrict fans from scraping the data from NHL.com and using it for their own websites. Becoming the sole source of data is likely their ideal vision, but they have to find a balance to ensure they play a role in the field of hockey analytics. Analytics is an excellent tool for fan engagement, so it would be in their best interest to keep the data open, easy to access and easy to use.

Professional sports leagues should really want their fans to be informed and to develop knowledge to whatever level they want. The league is much better served if they have a fanbase that’s free to interact with data, push any sort of hockey discussion and share their thoughts across their networks. That’s what fan engagement is at its very core.

Keep the Data Open

To put up any sort of barrier, whether it be a fee for data or technological restrictions, would be detrimental to the overall interaction between the game and its fans.

Knowledge and information will always be free. The barriers and the traditional models to keep data and information from the general public have been dropping in every aspect of our social world as the creativity of human beings will always get what it wants. Think of the illegal downloads of music and films; the open data projects of Governments and the death of encyclopedia books.

If the NHL does try to restrict access to data, you can be sure that fans will work together to collect the data themselves. The tools are available, the network is already established and the motivation for people to participate will be high. There are also companies collecting data of other sports that can quite easily adapt for hockey and begin collecting data at a  much larger scale.

Really, the NHL doesn’t stand a chance if they put a barrier to their data.

If you’re interested in learning more about collaborative online communities mixed with information/knowledge management topics, I highly recommend the following:

  • Benkler, Y. (2011). The Penguin and the Leviathan: The Triumph of Co-operation over Self-Interest. New York: Crown Business
  • Lessig, L. (2008). Remix: Making Art and Commerce Thrive in the Hybrid Economy. New York: Penguin Press.
  • Shirky, C. (2010). Cognitive Surplus. New York: Penguin Press.

Importance of Hockey Analytics II

Source: Zimbio

Source: Zimbio

Originally posted at Hockey in Society.

It’s been remarkable to see how quickly the field has developed over the past few years. The amount of new information being derived from hockey analytics has grown and continues to be discussed across a large and diverse online community. And while the focus has rightfully been on the hockey data and extracting meaningful patterns, it’s important to assess some of the foundational concepts that have supported the development and growing popularity of hockey analytics.

Analytics in any industry is a continuous process. Regardless of what patterns are found, new questions will arise to continue advancing the discussion initiated by analytics. Hockey analytics is no different as it really is a never ending process to uncover, share and build upon new information. Because it pertains to professional hockey, there is new data available almost every day and involves analysis from anyone that’s interested in the topic. The game itself, including the off-ice business (i.e., trades, free agency, draft) is highly chaotic and at times unpredictable.

Related: Importance of Hockey Analytics – Hockey in Society (2012, June 11)

What makes hockey analytics, or any sports analytics unique, is that it’s being done in an open environment that allows for anyone with basic analytic and communication technology tools to join the discussion. Using blogs and Twitter, participants have created a very collaborative environment that supports discussion and the continuous extension of ideas and information.

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